@article{abdelkader_2018,
title = {Robust H ∞ gain neuro-adaptive observer design for nonlinear uncertain systems},
author = {Abdelkader, K.; Krais, B.},
journal = {Transactions of the Institute of Measurement and Control},
year = {2108},
institution = {Higher Institute of Computer Science of Mahdia, Tunisia},
abstract = {To guarantee convergent state estimates and exact approximations, it is highly desirable that observers can independently dominate the effects of unmodelled dynamics. Based on adaptive nonlinear approximation, this paper presents a robust H∞ gain neuro-adaptive observer (RH∞GNAO) design methodology for a large class of uncertain nonlinear systems in the presence of time-varying unknown parameters with bounded external disturbances on the state vector and on the output of the original system. The proposed RH∞GNAO incorporates radial basis function neural networks (RBFNNs) to approximate the unknown nonlinearities in the uncertain system. The weight dynamics of every RBFNN are adjusted online by using an adaptive projection algorithm. The asymptotic convergence of the state and parameter estimation errors is achieved by using Lyapunov cogitation under a well-defined persistent excitation condition, and without recourse to the strictly positive real condition. The repercussions of unknown disturbances are reduced by integrating an H∞ gain performance criterion into the proposed estimation approach. The condition imposed by this proposed observer approach, such that all estimated signals are uniformly ultimately bounded, is expressed in the form of the linear matrix inequality problem and warrants the demanded performances. To evaluate the performance of the proposed observer, various simulations are presented. },
keywords = {Uncertain nonlinear systems, Lyapunov stability, disturbances, neural networks, adaptive observer, H-infinity, linear matrix inequality},
language = {English},
publisher = {SAGE}
}

To guarantee convergent state estimates and exact approximations, it is highly desirable that observers can independently dominate the effects of unmodelled dynamics. Based on adaptive nonlinear approximation, this paper presents a robust H∞ gain neuro-adaptive observer (RH∞GNAO) design methodology for a large class of uncertain nonlinear systems in the presence of time-varying unknown parameters with bounded external disturbances on the state vector and on the output of the original system. The proposed RH∞GNAO incorporates radial basis function neural networks (RBFNNs) to approximate the unknown nonlinearities in the uncertain system. The weight dynamics of every RBFNN are adjusted online by using an adaptive projection algorithm. The asymptotic convergence of the state and parameter estimation errors is achieved by using Lyapunov cogitation under a well-defined persistent excitation condition, and without recourse to the strictly positive real condition. The repercussions of unknown disturbances are reduced by integrating an H∞ gain performance criterion into the proposed estimation approach. The condition imposed by this proposed observer approach, such that all estimated signals are uniformly ultimately bounded, is expressed in the form of the linear matrix inequality problem and warrants the demanded performances. To evaluate the performance of the proposed observer, various simulations are presented.

@article{wang_2019,
title = {A computationally efficient dynamical model of fluidic soft actuators and its experimental verification},
author = {Wang, T.; Zhang, Y.; Zhu, Y.; Zhu, S.},
journal = {Mechatronics},
year = {2019},
month = {04},
volume = {58},
institution = {Zhejiang University, China},
abstract = {This work develops a computationally efficient dynamical model for fluidic bending soft actuators in consideration of distributed-mass effect. The model in universal form is based on the Lagrangian approach and the constant curvature assumption. Since the model parameters are dependent on actuator type, a case study on the soft actuator with fiber-reinforced structure is carried out due to its convenience in manufacture and resistance to trivial deformation. The expressions of strain energy, gravitational potential energy, kinetic energy and generalized force are derived with respect to a generalized coordinate defined by the bending angle of the soft actuator. Material deformation and fluidic volume variation are also considered and derived in the model. Additionally, Taylor series expansions are employed to reduce the model complexity by neglecting the high-order terms reasonably. Finally, an experimental setup for the soft actuator is built and a curvature sensor is utilized to detect the bending angle. Experiments under typical operating conditions are implemented to verify the model and the results show that the measured data are in good accordance with the predicted responses. The proposed dynamical model can serve as a basis for further model-based control algorithm design for fluidic soft actuators. },
keywords = {Dynamical model Bending actuators Computationally efficient Fluidic power Soft robotics},
language = {English},
publisher = {Elsevier Ltd.}
}

This work develops a computationally efficient dynamical model for fluidic bending soft actuators in consideration of distributed-mass effect. The model in universal form is based on the Lagrangian approach and the constant curvature assumption. Since the model parameters are dependent on actuator type, a case study on the soft actuator with fiber-reinforced structure is carried out due to its convenience in manufacture and resistance to trivial deformation. The expressions of strain energy, gravitational potential energy, kinetic energy and generalized force are derived with respect to a generalized coordinate defined by the bending angle of the soft actuator. Material deformation and fluidic volume variation are also considered and derived in the model. Additionally, Taylor series expansions are employed to reduce the model complexity by neglecting the high-order terms reasonably. Finally, an experimental setup for the soft actuator is built and a curvature sensor is utilized to detect the bending angle. Experiments under typical operating conditions are implemented to verify the model and the results show that the measured data are in good accordance with the predicted responses. The proposed dynamical model can serve as a basis for further model-based control algorithm design for fluidic soft actuators.

@article{harmanci_2019,
title = {A Novel Approach for 3D-Structural Identification through Video Recording: Magnified Tracking},
author = {Harmanci, Y.E.; Gülan, U.; Holzner, M.; Chatzi, E. },
journal = {Sensors},
year = {2019},
volume = {19},
number = {5},
institution = {ETH Zürich, Switzerland},
abstract = {Advancements in optical imaging devices and computer vision algorithms allow the exploration of novel diagnostic techniques for use within engineering systems. A recent field of application lies in the adoption of such devices for non-contact vibrational response recordings of structures, allowing high spatial density measurements without the burden of heavy cabling associated with conventional technologies. This, however, is not a straightforward task due to the typically low-amplitude displacement response of structures under ambient operational conditions. A novel framework, namely Magnified Tracking (MT), is proposed herein to overcome this limitation through the synergistic use of two computer vision techniques. The recently proposed phase-based motion magnification (PBMM) framework, for amplifying motion in a video within a defined frequency band, is coupled with motion tracking by means of particle tracking velocimetry (PTV). An experimental campaign was conducted to validate a proof-of-concept, where the dynamic response of a shear frame was measured both by conventional sensors as well as a video camera setup, and cross-compared to prove the feasibility of the proposed non-contact approach. The methodology was explored both in 2D and 3D configurations, with PTV revealing a powerful tool for the measurement of perceptible motion. When MT is utilized for tracking “imperceptible” structural responses (i.e., below PTV sensitivity), via the use of PBMM around the resonant frequencies of the structure, the amplified motion reveals the operational deflection shapes, which are otherwise intractable. The modal results extracted from the magnified videos, using PTV, demonstrate MT to be a viable non-contact alternative for 3D modal identification with the benefit of a spatially dense measurement grid. },
keywords = {vibration-based measurement; SHM; structural identification; motion magnification; particle tracking velocimetry},
language = {English},
publisher = {MDPI}
}

Advancements in optical imaging devices and computer vision algorithms allow the exploration of novel diagnostic techniques for use within engineering systems. A recent field of application lies in the adoption of such devices for non-contact vibrational response recordings of structures, allowing high spatial density measurements without the burden of heavy cabling associated with conventional technologies. This, however, is not a straightforward task due to the typically low-amplitude displacement response of structures under ambient operational conditions. A novel framework, namely Magnified Tracking (MT), is proposed herein to overcome this limitation through the synergistic use of two computer vision techniques. The recently proposed phase-based motion magnification (PBMM) framework, for amplifying motion in a video within a defined frequency band, is coupled with motion tracking by means of particle tracking velocimetry (PTV). An experimental campaign was conducted to validate a proof-of-concept, where the dynamic response of a shear frame was measured both by conventional sensors as well as a video camera setup, and cross-compared to prove the feasibility of the proposed non-contact approach. The methodology was explored both in 2D and 3D configurations, with PTV revealing a powerful tool for the measurement of perceptible motion. When MT is utilized for tracking “imperceptible” structural responses (i.e., below PTV sensitivity), via the use of PBMM around the resonant frequencies of the structure, the amplified motion reveals the operational deflection shapes, which are otherwise intractable. The modal results extracted from the magnified videos, using PTV, demonstrate MT to be a viable non-contact alternative for 3D modal identification with the benefit of a spatially dense measurement grid.

@article{huang_2019,
title = {A PSO-tuned Fuzzy Logic System for Position Tracking of Mobile Robot},
author = {Huang, C.; Farooq, U.; Liu, H.; Gu, J.; Luo, J.},
journal = {International Journal of Robotics and Automation},
year = {2019},
volume = {206},
abstract = {In this paper, we proposed a simple but practical fuzzy logic position tracking controller for a wheeled mobile robot. Certain mobile robot with symmetric or ignorable body shape may focus on its position precision on a path tracking task. In this case, we assigned its position errors as input of our fuzzy logic controller and its linear and angular velocities as outputs. Then, we optimized it by tuning the parameters of scaling and membership functions using a particle swarm optimization. Our fuzzy logic system was optimized and simulated in Matlab and Simulink and was experimentally tested on Quanser’s Qbot2 robot with Quarc control system. After optimization, the values of Fitness Function (cumulative position errors) have distinctly decreased from 35.9642 to 5.8246 in simulation and from 37.4041 to 7.3935 experimentally. These results had shown that the optimized system outperformed the same system without optimization. },
language = {English},
publisher = {Acta Press}
}

In this paper, we proposed a simple but practical fuzzy logic position tracking controller for a wheeled mobile robot. Certain mobile robot with symmetric or ignorable body shape may focus on its position precision on a path tracking task. In this case, we assigned its position errors as input of our fuzzy logic controller and its linear and angular velocities as outputs. Then, we optimized it by tuning the parameters of scaling and membership functions using a particle swarm optimization. Our fuzzy logic system was optimized and simulated in Matlab and Simulink and was experimentally tested on Quanser’s Qbot2 robot with Quarc control system. After optimization, the values of Fitness Function (cumulative position errors) have distinctly decreased from 35.9642 to 5.8246 in simulation and from 37.4041 to 7.3935 experimentally. These results had shown that the optimized system outperformed the same system without optimization.

@article{chan_2019,
title = {A smart mechatronic base isolation system using earthquake early warning},
author = {Chan, R.W.K.; Lin, Y.-S.; Tagawa, H.},
journal = {Soil Dynamics and Earthquake Engineering},
year = {2019},
month = {04},
volume = {119},
institution = {RMIT University, Australia; Hiroshima University, Japan},
abstract = {In earthquake-prone countries such as Japan, effects of earthquakes are one of the major design objectives in buildings and infrastructures. Recent advances in earthquake engineering have improved the safety and reliability of buildings and infrastructures. Better understanding of geomorphology of earthquakes also enables us to better predict and estimate propagation of such natural hazard. For example, the Earthquake Early Warning (EEW) system in Japan provides advanced warnings using the different arrival times of P and S waves. On the other hand, techniques and methods in passive, semi-active and active vibration control have flourished. Base-isolation is a proven technique which enhances earthquake resilience of buildings and bridges. In general, this technique involves decoupling a superstructure from its foundation and lengthens its natural period of vibration. This technique is mature and commercialization has taken place worldwide. However, wind-resistance of base-isolated structures is generally a concern as the lateral stiffness of a base-isolated structure is low and serviceability wind effects may induce unacceptable lateral movement and/or vibration of the structure. This paper presents a new concept which the base-isolation system is activated by EEW system through a mechatronic system. In other times the structure is not base-isolated and provides strong lateral resistance against wind loads. As a backup design, the proposed system also equips with its own network of accelerometers which can trigger base isolation system independent from EEW system. The smart mechatronic base isolation system is fully automated, and resets itself after each ground motion. The paper describes the conceptual framework of proposed system and presents laboratory-scaled proof-of-concept experiments. Four historical earthquake time histories were used as ground excitations. Structural responses are compared between the two triggering mechanisms and results are discussed. Finally, the concept of Internet of Things (IoT) which make use of EEW is discussed, allowing connectivity between a single control unit and a network of infrastructures to achieve economy of scale. },
keywords = {Smart structures, Base isolation, Earthquake early warning, Internet of things},
language = {English},
publisher = {Elsevier Ltd.},
pages = {299-307}
}

In earthquake-prone countries such as Japan, effects of earthquakes are one of the major design objectives in buildings and infrastructures. Recent advances in earthquake engineering have improved the safety and reliability of buildings and infrastructures. Better understanding of geomorphology of earthquakes also enables us to better predict and estimate propagation of such natural hazard. For example, the Earthquake Early Warning (EEW) system in Japan provides advanced warnings using the different arrival times of P and S waves. On the other hand, techniques and methods in passive, semi-active and active vibration control have flourished. Base-isolation is a proven technique which enhances earthquake resilience of buildings and bridges. In general, this technique involves decoupling a superstructure from its foundation and lengthens its natural period of vibration. This technique is mature and commercialization has taken place worldwide. However, wind-resistance of base-isolated structures is generally a concern as the lateral stiffness of a base-isolated structure is low and serviceability wind effects may induce unacceptable lateral movement and/or vibration of the structure. This paper presents a new concept which the base-isolation system is activated by EEW system through a mechatronic system. In other times the structure is not base-isolated and provides strong lateral resistance against wind loads. As a backup design, the proposed system also equips with its own network of accelerometers which can trigger base isolation system independent from EEW system. The smart mechatronic base isolation system is fully automated, and resets itself after each ground motion. The paper describes the conceptual framework of proposed system and presents laboratory-scaled proof-of-concept experiments. Four historical earthquake time histories were used as ground excitations. Structural responses are compared between the two triggering mechanisms and results are discussed. Finally, the concept of Internet of Things (IoT) which make use of EEW is discussed, allowing connectivity between a single control unit and a network of infrastructures to achieve economy of scale.

@article{jeon_2019,
title = {A Stealthy Sensor Attack for Uncertain Cyber-Physical Systems},
author = {Jeon, H.; Eu, Y.},
journal = {Internet of Things Journal},
year = {2019},
institution = {DGIST, South Korea},
abstract = { In this paper, we present a sensor attack on Cyber-Physical Systems (CPS), which can be constructed with limited knowledge of the target system and can remain stealthy until the attack succeeds. The target CPS consists of a physical plant with unstable linear dynamics and a feedback controller. Specifically, the attack mechanism is to impede the stabilizing function of the feedback controller by injecting false data to the sensors where the false data are created using the unstable dynamics of the plant. When the only nominal model for the target dynamics is known, the stealthiness is maintained by deploying a mechanism similar to a disturbance observer which can be designed to absorb the effect of the mismatch between the nominal and actual dynamics until the attack succeeds. The success of the attack is defined by the norm of the system state exceeding a threshold. Sensor attacks that exploit unstable plant dynamics had been conceived previously. Generation of such attacks require precise knowledge of the target system for stealthiness, i.e., the attack must cancel at the sensor exactly the effect of instability in order to avoid detection. When not exact, the mismatch grows exponentially leading to the detection of abnormality. The attack presented in this work absorbs the mismatch using the disturbance observer mechanism, where the degree of absorption is selected such that the detection is delayed until the attack succeeds. Thus, the proposed attack, compared to the conventional ones, poses a greater level of threat to CPS. In this work, generation of the attack is presented, and the effect is analyzed. The consequence of the attack is illustrated and emphasized by simulations on quadrotors and inverted pendulums, respectively. },
issn = {2327-4662 },
keywords = {Cyber-physical systems, stealthy sensor attack, Model uncertainty},
language = {English},
publisher = {IEEE}
}

In this paper, we present a sensor attack on Cyber-Physical Systems (CPS), which can be constructed with limited knowledge of the target system and can remain stealthy until the attack succeeds. The target CPS consists of a physical plant with unstable linear dynamics and a feedback controller. Specifically, the attack mechanism is to impede the stabilizing function of the feedback controller by injecting false data to the sensors where the false data are created using the unstable dynamics of the plant. When the only nominal model for the target dynamics is known, the stealthiness is maintained by deploying a mechanism similar to a disturbance observer which can be designed to absorb the effect of the mismatch between the nominal and actual dynamics until the attack succeeds. The success of the attack is defined by the norm of the system state exceeding a threshold. Sensor attacks that exploit unstable plant dynamics had been conceived previously. Generation of such attacks require precise knowledge of the target system for stealthiness, i.e., the attack must cancel at the sensor exactly the effect of instability in order to avoid detection. When not exact, the mismatch grows exponentially leading to the detection of abnormality. The attack presented in this work absorbs the mismatch using the disturbance observer mechanism, where the degree of absorption is selected such that the detection is delayed until the attack succeeds. Thus, the proposed attack, compared to the conventional ones, poses a greater level of threat to CPS. In this work, generation of the attack is presented, and the effect is analyzed. The consequence of the attack is illustrated and emphasized by simulations on quadrotors and inverted pendulums, respectively.

@article{chairez_2019,
title = {Adaptive control schemes applied to a control moment gyroscope of 2 degrees of freedom},
author = {Montoya–Cháirez, J.; Santibáñez, V.; Moreno–Valenzuela, J.},
journal = {Mechatronics},
year = {2019},
month = {02},
volume = {57},
institution = {Instituto Politécnico Nacional–CITEDI, Mexico; Instituto Tecnológico de La Laguna, Mexico},
abstract = {Control of underactuated mechanical systems has been an important trend in mechatronics and nonlinear systems. Typical examples are the Furuta pendulum and inertia wheel pendulum. On the other hand, gyroscopes are important in aerial and space systems. In this paper, a two-degree of freedom underactuated control moment gyroscope (CMG) is studied. This system is highly coupled of one joint to the another and is difficult to control, which make it an important benchmark system. The problem addressed in this paper is to achieve robust motion control of the underactuated CMG. Firstly, a trajectory tracking controller is developed by using the feedback linearization technique. Secondly, two new adaptive algorithms are introduced, which correspond to an adaptive neural network algorithm and an adaptive model regressor scheme. A real–time experimental comparison is carried out among a linear PD control law, a cascade PID-PID controller and the introduced schemes. The real-time experimental study validates the introduced theory, where the performance of the controllers is evaluated with and without a periodic disturbance at the input. },
keywords = {Control moment gyroscope, Underactuated systems, Trajectory tracking control, Adaptive control, Real–time experiments},
language = {English},
publisher = {Elsevier Ltd.},
pages = {73-85}
}

Control of underactuated mechanical systems has been an important trend in mechatronics and nonlinear systems. Typical examples are the Furuta pendulum and inertia wheel pendulum. On the other hand, gyroscopes are important in aerial and space systems. In this paper, a two-degree of freedom underactuated control moment gyroscope (CMG) is studied. This system is highly coupled of one joint to the another and is difficult to control, which make it an important benchmark system. The problem addressed in this paper is to achieve robust motion control of the underactuated CMG. Firstly, a trajectory tracking controller is developed by using the feedback linearization technique. Secondly, two new adaptive algorithms are introduced, which correspond to an adaptive neural network algorithm and an adaptive model regressor scheme. A real–time experimental comparison is carried out among a linear PD control law, a cascade PID-PID controller and the introduced schemes. The real-time experimental study validates the introduced theory, where the performance of the controllers is evaluated with and without a periodic disturbance at the input.

@article{niu_2018,
title = {Adaptive vibration suppression of time-varying structures with enhanced FxLMS algorithm},
author = {Niu, W.; Zou, C.; Li, B.; Wanga, W.},
journal = {Mechanical Systems and Signal Processing},
year = {2019},
month = {03},
volume = {118},
institution = {Northwestern Polytechnical University, China; Ohio State University, USA},
abstract = {Filtered-x least mean square (FxLMS) control algorithm has been widely used for adaptive noise and vibration control. Yet, classical FxLMS controller is not applicable for time-varying system since the secondary path identified offline cannot reflect the system characteristics in real-time. In order to overcome this challenge, here online modelling of secondary path is realized by existing signals, i.e. no noise injection. In addition, FxLMS is further enhanced with variable step size that is adaptively adjusted via bang-bang controller. The adaptation of step size is aimed to achieve the balance between control efficiency and system stability. To verify the feasibility of proposed control algorithm, numerical and experimental efforts are undertaken for the buffeting suppression of vertical tail which is a typical time-varying system. Both results demonstrate that the proposed method is able to reduce the vibration response effectively for varied structures under harmonic and random excitations, while the classical FxLMS cannot. This performance improvement indicates that the online modeling of secondary path captures the system characteristics accurately and timely. Moreover, compared with the FxLMS controller with fixed step size, the control efficiency of the proposed method is also strengthened. These multiple enhancements of the performance of FxLMS controller reveal that online modeling and variable step size are favorable for adaptive vibration control of time-varying structures. },
keywords = {Filtered-x least mean square, Bang-bang control, Variable step size, Online identification, Time-varying structures},
language = {English},
publisher = {Elsevier Ltd.}
}

Filtered-x least mean square (FxLMS) control algorithm has been widely used for adaptive noise and vibration control. Yet, classical FxLMS controller is not applicable for time-varying system since the secondary path identified offline cannot reflect the system characteristics in real-time. In order to overcome this challenge, here online modelling of secondary path is realized by existing signals, i.e. no noise injection. In addition, FxLMS is further enhanced with variable step size that is adaptively adjusted via bang-bang controller. The adaptation of step size is aimed to achieve the balance between control efficiency and system stability. To verify the feasibility of proposed control algorithm, numerical and experimental efforts are undertaken for the buffeting suppression of vertical tail which is a typical time-varying system. Both results demonstrate that the proposed method is able to reduce the vibration response effectively for varied structures under harmonic and random excitations, while the classical FxLMS cannot. This performance improvement indicates that the online modeling of secondary path captures the system characteristics accurately and timely. Moreover, compared with the FxLMS controller with fixed step size, the control efficiency of the proposed method is also strengthened. These multiple enhancements of the performance of FxLMS controller reveal that online modeling and variable step size are favorable for adaptive vibration control of time-varying structures.

@inproceedings{kasimzade_2019,
title = {Analytical and Experimental Modal Analysis of a Model Cold Formed Steel (CFS) Structures Using Microtremor Excitation},
author = {Kasimzade A.A.; Tuhta S.; Atmaca G.; Ozdemir S.},
booktitle = {Seismic Isolation, Structural Health Monitoring, and Performance Based Seismic Design in Earthquake Engineering},
year = {2019},
institution = {Ondokuz Mayis University, Turkey},
abstract = {In this study was investigated the possibility of using the recorded micro-tremor data on ground level as ambient vibration input excitation data for investigation and application Operational Modal Analysis (OMA) on the bench-scale earthquake simulator (The Quanser Shake Table) for model cold formed steel (cfs) structures. As known OMA methods (such as EFDD, SSI and so on) are supposed to deal with the ambient responses. For this purpose, analytical and experimental modal analysis of a model (cfs) structure for dynamic characteristics was evaluated. 3D Finite element model of the building was evaluated for the model (cfs) structure based on the design drawing. Ambient excitation was provided by shake table from the recorded micro tremor ambient vibration data on ground level. Enhanced Frequency Domain Decomposition is used for the output-only modal identification. From this study, best correlation is found between mode shapes. Natural frequencies and analytical frequencies in average (only) 2.99% are differences. },
keywords = {Experimental modal analysis, Modal parameter, EFDD, Shake table },
language = {English},
publisher = {Springer, Cham},
isbn = {978-3-319-93156-2},
pages = {217-231}
}

In this study was investigated the possibility of using the recorded micro-tremor data on ground level as ambient vibration input excitation data for investigation and application Operational Modal Analysis (OMA) on the bench-scale earthquake simulator (The Quanser Shake Table) for model cold formed steel (cfs) structures. As known OMA methods (such as EFDD, SSI and so on) are supposed to deal with the ambient responses. For this purpose, analytical and experimental modal analysis of a model (cfs) structure for dynamic characteristics was evaluated. 3D Finite element model of the building was evaluated for the model (cfs) structure based on the design drawing. Ambient excitation was provided by shake table from the recorded micro tremor ambient vibration data on ground level. Enhanced Frequency Domain Decomposition is used for the output-only modal identification. From this study, best correlation is found between mode shapes. Natural frequencies and analytical frequencies in average (only) 2.99% are differences.

@conference{yildrim_2019,
title = {Application of a Distributed Adaptive Control Approach to a Heterogeneous Multiagent Mechanical Platform},
author = {Yildirim, E.; Sarsilmaz, S.B.; Yucelen, T.},
booktitle = {AIAA Scitech 2019 Forum},
year = {2019},
institution = {University of South Florida, FL, USA},
abstract = {A distributed adaptive control architecture is recently developed for a class of heterogeneous uncertain multiagent systems [1]. This architecture has the capability to provide uniform ultimate boundedness for the output tracking error between each heterogeneous uncertain agent and the leader with unknown dynamics. As a special case, in addition, it allows the output of agents to asymptotically converge to the output of the leader, which converges to a constant, in the presence of matched disturbances and time-invariant system uncertainties over fixed and directed communication graph topologies. The main contribution of this paper is to provide an experimental study on a heterogeneous multiagent mechanical platform composed of two cart-inverted pendulums and a cart to demonstrate the performance of this architecture in practice. },
language = {English},
publisher = {AIAA}
}

A distributed adaptive control architecture is recently developed for a class of heterogeneous uncertain multiagent systems [1]. This architecture has the capability to provide uniform ultimate boundedness for the output tracking error between each heterogeneous uncertain agent and the leader with unknown dynamics. As a special case, in addition, it allows the output of agents to asymptotically converge to the output of the leader, which converges to a constant, in the presence of matched disturbances and time-invariant system uncertainties over fixed and directed communication graph topologies. The main contribution of this paper is to provide an experimental study on a heterogeneous multiagent mechanical platform composed of two cart-inverted pendulums and a cart to demonstrate the performance of this architecture in practice.

@article{yang_2019,
title = {Attitude Synchronization for Multiple 3-DOF Helicopters with Actuator Faults},
author = {Yang, H.; Jiang, B.; Liu, H.H.T.; Yang, H.; Zhang, Q.},
journal = {IEEE/ASME Transactions on Mechatronics},
year = {2019},
institution = {Nanjing University of Aeronautics and Astronautics, China; Institute for Aerospace Studies, University of Toronto, Canada},
abstract = {The attitude synchronization for multiple three-degree-of-freedom (3-DOF) helicopters in the presence of system uncertainties and time-varying actuator faults is investigated. A fault tolerant cooperative control algorithm based on robust adaptive control is proposed to synchronize attitudes of multiple helicopter systems in the case where some of the helicopters are subjected to both partial losses of control effectiveness and additive actuator faults. The proposed design is a distributed control method which allows each vehicle to track external reference signals merely in light of its neighborhood information. With the proposed design, time-varying actuator faults are tolerated without sacrificing the attitude synchronization performance. The effectiveness of the proposed control method is verified via a comparative experimental study. },
issn = {1083-4435},
keywords = {Fault tolerant control, cooperative control, three degree-of-freedom helicopter, adaptive control, robust control},
language = {English},
publisher = {IEEE}
}

The attitude synchronization for multiple three-degree-of-freedom (3-DOF) helicopters in the presence of system uncertainties and time-varying actuator faults is investigated. A fault tolerant cooperative control algorithm based on robust adaptive control is proposed to synchronize attitudes of multiple helicopter systems in the case where some of the helicopters are subjected to both partial losses of control effectiveness and additive actuator faults. The proposed design is a distributed control method which allows each vehicle to track external reference signals merely in light of its neighborhood information. With the proposed design, time-varying actuator faults are tolerated without sacrificing the attitude synchronization performance. The effectiveness of the proposed control method is verified via a comparative experimental study.

@article{fu_2019,
title = {Comparative studies of vibration control effects between structures with particle dampers and tuned liquid dampers using substructure shake table testing methods},
author = {Fu, B.; Jiang, H.; Wu, T.},
journal = {Soil Dynamics and Earthquake Engineering},
year = {2019},
month = {06},
volume = {121},
institution = {Chang’an University, China; Tongji University, China},
abstract = {This paper compares the vibration control performance of particle dampers (PDs) and tuned liquid dampers (TLDs) by using the up-to-date substructure shake table testing (SSTT) method. In implementing the SSTT, three representative model-based integration algorithms, whose algorithmic parameters are functions of the complete model of the structure system to enable unconditional stability to be achieved within the framework of an explicit formulation, are adopted. The experimental procedures of the SSTT methods using the three integration algorithms are presented. The SSTT system of the single-degree-of-freedom (SDOF) structures with PDs/TLDs is constructed and verified by comparing the experimental results of the SSTTs and the corresponding complete structure shake table tests. The vibration reduction effects of PDs and TLDs with the same mass ratio are investigated and compared by conducting a series of SSTTs of the SDOF systems with such devices under the excitation of ground motion. The influences of mass ratio, damping ratio and structural frequency on control efficiency of PDs and TLDs are studied. The results from the parametric analyses demonstrate that all the aforementioned factors have significant impacts on the vibration control performance of both dampers. Most experimental results indicate that the PDs have better vibration control performance than the counterpart TLDs. },
keywords = {Substructure shake table testing, Particle damper, Tuned liquid damper, Vibration control, Integration algorithm},
language = {English},
publisher = {Elsevier B.V.},
pages = {421-435}
}

This paper compares the vibration control performance of particle dampers (PDs) and tuned liquid dampers (TLDs) by using the up-to-date substructure shake table testing (SSTT) method. In implementing the SSTT, three representative model-based integration algorithms, whose algorithmic parameters are functions of the complete model of the structure system to enable unconditional stability to be achieved within the framework of an explicit formulation, are adopted. The experimental procedures of the SSTT methods using the three integration algorithms are presented. The SSTT system of the single-degree-of-freedom (SDOF) structures with PDs/TLDs is constructed and verified by comparing the experimental results of the SSTTs and the corresponding complete structure shake table tests. The vibration reduction effects of PDs and TLDs with the same mass ratio are investigated and compared by conducting a series of SSTTs of the SDOF systems with such devices under the excitation of ground motion. The influences of mass ratio, damping ratio and structural frequency on control efficiency of PDs and TLDs are studied. The results from the parametric analyses demonstrate that all the aforementioned factors have significant impacts on the vibration control performance of both dampers. Most experimental results indicate that the PDs have better vibration control performance than the counterpart TLDs.

@article{narayanamoorthi_2019,
title = {Cross Interference Minimization and Simultaneous Wireless Power Transfer to Multiple Frequency Loads Using Frequency Bifurcation Approach},
author = {Narayanamoorthi R.; Vimala Juliet A.; Bharatiraja, C.},
journal = {IEEE Transactions on Power Electronics},
year = {2019},
institution = {SRM Institute of Science and Technology, India},
abstract = {Simultaneous power distribution to multiple loads using a single source in the wireless power transfer (WPT) system is a challenging issue due to cross-coupling between the load coils, which reduces the power transfer efficiency. In a resonant WPT system, when two or more coils operated under over coupled (OC) condition, the original operating resonant frequency gets bifurcated, and thereby reduction in the power transfer efficiency. Different techniques are investigated in the literature to mitigate the frequency bifurcation phenomena in the resonant WPT system. However, the utilization of frequency bifurcation approach for the simultaneous power transfer to multiple loads is not addressed. This paper proposes a simultaneous power transfer approach using frequency bifurcation for the multiple load system designed with different operating frequency. Mathematical, simulation and experimental studies performed for dual, triple, and four coil WPT systems with multiple loads. In addition, an automatic power flow control method is implemented to estimate the load current from the source, which helps to select a new set of load coils to be charged. The experimental results confirm the proposed power transfer, helps to attain higher power transfer efficiency of 39.34%, 49.31%, 68.22% and cross interference of -31.2 dBV, -36.2 dBV, -41.2 dBV for dual, triple, and four coil WPT system respectively. },
keywords = {Wireless Power, Selective Wireless Power Transfer, Multiple receivers, Simultaneous power transfer, Frequency Bifurcation},
language = {English},
publisher = {IEEE}
}

Simultaneous power distribution to multiple loads using a single source in the wireless power transfer (WPT) system is a challenging issue due to cross-coupling between the load coils, which reduces the power transfer efficiency. In a resonant WPT system, when two or more coils operated under over coupled (OC) condition, the original operating resonant frequency gets bifurcated, and thereby reduction in the power transfer efficiency. Different techniques are investigated in the literature to mitigate the frequency bifurcation phenomena in the resonant WPT system. However, the utilization of frequency bifurcation approach for the simultaneous power transfer to multiple loads is not addressed. This paper proposes a simultaneous power transfer approach using frequency bifurcation for the multiple load system designed with different operating frequency. Mathematical, simulation and experimental studies performed for dual, triple, and four coil WPT systems with multiple loads. In addition, an automatic power flow control method is implemented to estimate the load current from the source, which helps to select a new set of load coils to be charged. The experimental results confirm the proposed power transfer, helps to attain higher power transfer efficiency of 39.34%, 49.31%, 68.22% and cross interference of -31.2 dBV, -36.2 dBV, -41.2 dBV for dual, triple, and four coil WPT system respectively.

@article{huang2_2019,
title = {Data-Driven Backstepping Control of Underactuated Mechanical Systems},
booktitle = {Huang, J.; Zhang, T.; Sun, J.-Q.},
journal = {Journal of Dynamic Systems, Measurement and Control},
year = {2019},
institution = {Beijing University of Chemical Technology, China; University of California, Merced, CA, USA},
abstract = {This paper studies control problems of underactuated mechanical systems with model uncertainties. The control is designed with the method of backstepping. The first-order low-pass filters are used to estimate the unknown quantities and to avoid the ``explosion of terms''. A novel method is also proposed to implement the control without the knowledge of the control coefficient, which makes the whole process of backstepping control data-driven. The stability of the proposed control in the Lyapunov sense is studied. It is numerically and experimentally validated, and compared with the well-known model-based LQR control. The data-driven backstepping control is found to provide comparable performances to that of the LQR control with the advantage of being model-free and robust. },
keywords = {Backstepping; Underactuated mechanical systems; Tracking control; Datadriven; Flexible link},
language = {English},
publisher = {ASME}
}

This paper studies control problems of underactuated mechanical systems with model uncertainties. The control is designed with the method of backstepping. The first-order low-pass filters are used to estimate the unknown quantities and to avoid the ``explosion of terms''. A novel method is also proposed to implement the control without the knowledge of the control coefficient, which makes the whole process of backstepping control data-driven. The stability of the proposed control in the Lyapunov sense is studied. It is numerically and experimentally validated, and compared with the well-known model-based LQR control. The data-driven backstepping control is found to provide comparable performances to that of the LQR control with the advantage of being model-free and robust.

@article{li2_2019,
title = {Decentralized Trajectory Tracking Control for Modular and Reconfigurable Robots With Torque Sensor: Adaptive Terminal Sliding Control-Based Approach},
author = {Li, Y.; Lu, Z.; Zhou, F.; Dong, B.; Liu, K.; Li, Y. },
journal = {Journal of Dynamic Systems, Measurement, and Control},
year = {2019},
volume = {141},
number = {6},
institution = {Changchun University of Technology, China},
abstract = {The main technical challenge in decentralized control of modular and reconfigurable robots (MRRs) with torque sensor is related to the treatment of interconnection term and friction term. This paper proposed a modified adaptive sliding mode decentralized control strategy for trajectory tracking control of the MRRs. The radial basis function (RBF) neural network is used as an effective learning method to approximate the interconnection term and friction term, eliminating the effect of model uncertainty and reducing the controller gain. In addition, in order to provide faster convergence and higher precision control, the terminal sliding mode algorithm is introduced to the controller design. Based on the Lyapunov method, the stability of the MRRs is proved. Finally, experiments are performed to confirm the effectiveness of the method. },
keywords = {Friction, Sensors, Control equipment, Robots, Trajectories (Physics), Design, Artificial neural networks, Errors, Torque, Tracking control},
language = {English},
publisher = {ASME}
}

The main technical challenge in decentralized control of modular and reconfigurable robots (MRRs) with torque sensor is related to the treatment of interconnection term and friction term. This paper proposed a modified adaptive sliding mode decentralized control strategy for trajectory tracking control of the MRRs. The radial basis function (RBF) neural network is used as an effective learning method to approximate the interconnection term and friction term, eliminating the effect of model uncertainty and reducing the controller gain. In addition, in order to provide faster convergence and higher precision control, the terminal sliding mode algorithm is introduced to the controller design. Based on the Lyapunov method, the stability of the MRRs is proved. Finally, experiments are performed to confirm the effectiveness of the method.

@conference{kim_2019,
title = {Deep Q-Network Based Rotary Inverted Pendulum System and Its Monitoring on the EdgeX Platform},
author = {Kim, J.-B.; Lim, H.-K.; Kwon, D.-H.; Kim, M.-S.; Hong, Y.-G.; Han, Y.-H. },
booktitle = {2019 International Conference on Artificial Intelligence in Information and Communication (ICAIIC)},
year = {2019},
institution = {Korea University of Technology and Education, Korea; Electronics and Telecommunications Research Institute, Korea},
abstract = {A rotary inverted pendulum is an unstable and highly nonlinear device and is used as a common model for engineering applications in linear and nonlinear control. In this study, we created a cyber physical system (CPS) to demonstrate that a deep reinforcement learning agent using a rotary inverted pendulum can successfully control a remotely located physical device. The device we created is composed of a cyber environment and physical environment using the Message Queuing Telemetry Transport (MQTT) protocol with an Ethernet connection to connect the cyber environment and the physical environment. The reinforcement learning agent controls the physical device, which is located remotely from the controller and a classical proportional integral derivative (PID) controller is utilized to implement imitation and reinforcement learning and facilitate the learning process. In addition, the control and monitoring system is built on the open source EdgeX platform, so that learning tasks performed near the source of data generation and real-time data emitted from the physical device can be observed while reinforcement learning is performed. From our CPS experimental system, we verify that a deep reinforcement learning agent can control a remotely located real-world device successfully. },
keywords = {EdgeX, Deep Q-Network (DQN), Deep Reinforcement Learning, Rotary Inverted Pendulum},
language = {English},
publisher = {IEEE},
isbn = {978-1-5386-7823-7 }
}

A rotary inverted pendulum is an unstable and highly nonlinear device and is used as a common model for engineering applications in linear and nonlinear control. In this study, we created a cyber physical system (CPS) to demonstrate that a deep reinforcement learning agent using a rotary inverted pendulum can successfully control a remotely located physical device. The device we created is composed of a cyber environment and physical environment using the Message Queuing Telemetry Transport (MQTT) protocol with an Ethernet connection to connect the cyber environment and the physical environment. The reinforcement learning agent controls the physical device, which is located remotely from the controller and a classical proportional integral derivative (PID) controller is utilized to implement imitation and reinforcement learning and facilitate the learning process. In addition, the control and monitoring system is built on the open source EdgeX platform, so that learning tasks performed near the source of data generation and real-time data emitted from the physical device can be observed while reinforcement learning is performed. From our CPS experimental system, we verify that a deep reinforcement learning agent can control a remotely located real-world device successfully.

@article{murali_2019,
title = {Design and evaluation of a distally actuated powered finger prosthesis with self-contained transmission for individuals with partial hand loss},
author = {Murali, B.; Huddle, S.; Weir, R.F.},
journal = {Advances in Mechanical Engineering},
year = {2019},
volume = {11},
number = {4},
institution = {Rice University, USA; University of Colorado at Denver, USA},
abstract = {Partial hand loss accounts for the overwhelming majority of upper limb deficiencies. Despite this, individuals with partial hand loss have a limited number of prosthetic options at their disposal. Existing externally powered devices typically house both motor and gear transmission in the proximal phalanx, which provides function at the expense of anthropomorphism. We present a novel design for an externally powered finger prosthesis with a custom gear transmission that is capable of higher intermittent torques compared to commercial gearheads of equivalent volume. We manufacture a fully functional transmission using a high-strength maraging steel alloy and direct laser metal sintering. The transmission consists of multiple planetary and spur gear stages arranged in a stackable (or laminar) configuration and accommodates joint movement at the proximal interphalangeal joint. The powered finger is equivalent in size to a 50th percentile female index finger and is capable of generating pinch forces comparable to those of commercial powered fingers at flexion speeds that exceed those of existing devices. While there are several practical and functional improvements for future iterations, our design represents a viable option for a powered finger capable of accommodating a wide range of individuals with partial hand loss. },
keywords = {Powered finger, partial hand loss, amputation, prosthesis, transmissions, prosthetic hand, assistive device},
language = {English},
publisher = {SAGE}
}

Partial hand loss accounts for the overwhelming majority of upper limb deficiencies. Despite this, individuals with partial hand loss have a limited number of prosthetic options at their disposal. Existing externally powered devices typically house both motor and gear transmission in the proximal phalanx, which provides function at the expense of anthropomorphism. We present a novel design for an externally powered finger prosthesis with a custom gear transmission that is capable of higher intermittent torques compared to commercial gearheads of equivalent volume. We manufacture a fully functional transmission using a high-strength maraging steel alloy and direct laser metal sintering. The transmission consists of multiple planetary and spur gear stages arranged in a stackable (or laminar) configuration and accommodates joint movement at the proximal interphalangeal joint. The powered finger is equivalent in size to a 50th percentile female index finger and is capable of generating pinch forces comparable to those of commercial powered fingers at flexion speeds that exceed those of existing devices. While there are several practical and functional improvements for future iterations, our design represents a viable option for a powered finger capable of accommodating a wide range of individuals with partial hand loss.

@article{tang_2019,
title = {Design and Kinematic Control of the Cable-Driven Hyper-Redundant Manipulator for Potential Underwater Applications},
author = {Tang, J.; Zhang, Y.; Huang, F.; Li, J.; Chen, Z.; Song, W.; Zhu, S.; Gu, J.},
journal = {Journal of Applied Sciences},
year = {2019},
volume = {9},
number = {6},
institution = {Zhejiang University, China; Dalhousie University, NS, Canada},
abstract = {Underwater manipulators are important robotic tools in the exploration of the ocean environment. Up to now, most existing underwater manipulators are rigid and with fixed 5 or 7 degrees of freedom (DOF), which may not be very suitable for some complicated underwater scenarios (e.g., pipe networks, narrow deep cavities, etc.). The biomimetic concept of muscles and tendons is also considered as continuum manipulators, but load capacity and operation accuracy are their essential drawbacks and thus limit their practical applications. Recently, the cable-driven technique has been developed for manipulators, which can include numerous joints and hyper-redundant DOF to execute tasks with dexterity and adaptability and thus they have strong potential for these complex underwater applications. In this paper, the design of a novel cable-driven hyper-redundant manipulator (CDHRM) is introduced, which is driven by multiple cables passing through the tubular structure from the base to the end-effector, and the joint numbers can be extended and decided by the specific underwater task requirements. The kinematic analysis of the proposed CDHRM is given which includes two parts: the cable-joint kinematics and the joint-end kinematics. The geometric relationship between the cable length and the joint angles are derived via the established geometric model for the cable-joint kinematics, and the projection relationship between the joint angles and end-effector’s pose is established via the spatial coordinate transformation matrix for the joint-end kinematics. Thus, the complex mapping relationships among the cables, joints and end-effectors are clearly achieved. To implement precise control, the kinematic control scheme is developed for the CDHRM with series-parallel connections and hyper-redundancy to achieve good tracking performance. The experiment on a real CDHRM system with five joints is carried out and the results verify the accuracy of kinematics solution, and the effectiveness of the proposed control design. Particularly, three experiments are tested in the underwater environment, which verifies its good tracking performance, load carrying and grasping capacity. },
issn = {2076-3417},
keywords = {hyper redundancy; cable-driven manipulator; mechanical design; kinematics},
language = {English},
publisher = {MDPI},
pages = {1142-1161}
}

Underwater manipulators are important robotic tools in the exploration of the ocean environment. Up to now, most existing underwater manipulators are rigid and with fixed 5 or 7 degrees of freedom (DOF), which may not be very suitable for some complicated underwater scenarios (e.g., pipe networks, narrow deep cavities, etc.). The biomimetic concept of muscles and tendons is also considered as continuum manipulators, but load capacity and operation accuracy are their essential drawbacks and thus limit their practical applications. Recently, the cable-driven technique has been developed for manipulators, which can include numerous joints and hyper-redundant DOF to execute tasks with dexterity and adaptability and thus they have strong potential for these complex underwater applications. In this paper, the design of a novel cable-driven hyper-redundant manipulator (CDHRM) is introduced, which is driven by multiple cables passing through the tubular structure from the base to the end-effector, and the joint numbers can be extended and decided by the specific underwater task requirements. The kinematic analysis of the proposed CDHRM is given which includes two parts: the cable-joint kinematics and the joint-end kinematics. The geometric relationship between the cable length and the joint angles are derived via the established geometric model for the cable-joint kinematics, and the projection relationship between the joint angles and end-effector’s pose is established via the spatial coordinate transformation matrix for the joint-end kinematics. Thus, the complex mapping relationships among the cables, joints and end-effectors are clearly achieved. To implement precise control, the kinematic control scheme is developed for the CDHRM with series-parallel connections and hyper-redundancy to achieve good tracking performance. The experiment on a real CDHRM system with five joints is carried out and the results verify the accuracy of kinematics solution, and the effectiveness of the proposed control design. Particularly, three experiments are tested in the underwater environment, which verifies its good tracking performance, load carrying and grasping capacity.

@article{kutuk_2019,
title = {Design of a robot-assisted exoskeleton for passive wrist and forearm rehabilitation},
author = {Kütük, M.E.; Dülger, L.C.; Daş, M.T.},
journal = {Journal of Mechanical Sciences},
year = {2019},
volume = {10},
number = {1},
institution = {Gaziantep University, Turkey; Izmir University of Economics, Turkey; University of Waterloo, Canada},
abstract = {This paper presents a new exoskeleton design for wrist and forearm rehabilitation. The contribution of this study is to offer a methodology which shows how to adapt a serial manipulator that reduces the number of actuators used on exoskeleton design for the rehabilitation. The system offered is a combination of end-effector- and exoskeleton-based devices. The passive exoskeleton is attached to the end effector of the manipulator, which provides motion for the purpose of rehabilitation process. The Denso VP 6-Axis Articulated Robot is used to control motion of the exoskeleton during the rehabilitation process. The exoskeleton is designed to be used for both wrist and forearm motions. The desired moving capabilities of the exoskeleton are flexion–extension (FE) and adduction–abduction (AA) motions for the wrist and pronation–supination (PS) motion for the forearm. The anatomical structure of a human limb is taken as a constraint during the design. The joints on the exoskeleton can be locked or unlocked manually in order to restrict or enable the movements. The parts of the exoskeleton include mechanical stoppers to prevent the excessive motion. One passive degree of freedom (DOF) is added in order to prevent misalignment problems between the axes of FE and AA motions. Kinematic feedback of the experiments is performed by using a wireless motion tracker assembled on the exoskeleton. The results proved that motion transmission from robot to exoskeleton is satisfactorily achieved. Instead of different exoskeletons in which each axis is driven and controlled separately, one serial robot with adaptable passive exoskeletons is adequate to facilitate rehabilitation exercises. },
language = {English},
publisher = {Copernicus Publications}
}

This paper presents a new exoskeleton design for wrist and forearm rehabilitation. The contribution of this study is to offer a methodology which shows how to adapt a serial manipulator that reduces the number of actuators used on exoskeleton design for the rehabilitation. The system offered is a combination of end-effector- and exoskeleton-based devices. The passive exoskeleton is attached to the end effector of the manipulator, which provides motion for the purpose of rehabilitation process. The Denso VP 6-Axis Articulated Robot is used to control motion of the exoskeleton during the rehabilitation process. The exoskeleton is designed to be used for both wrist and forearm motions. The desired moving capabilities of the exoskeleton are flexion–extension (FE) and adduction–abduction (AA) motions for the wrist and pronation–supination (PS) motion for the forearm. The anatomical structure of a human limb is taken as a constraint during the design. The joints on the exoskeleton can be locked or unlocked manually in order to restrict or enable the movements. The parts of the exoskeleton include mechanical stoppers to prevent the excessive motion. One passive degree of freedom (DOF) is added in order to prevent misalignment problems between the axes of FE and AA motions. Kinematic feedback of the experiments is performed by using a wireless motion tracker assembled on the exoskeleton. The results proved that motion transmission from robot to exoskeleton is satisfactorily achieved. Instead of different exoskeletons in which each axis is driven and controlled separately, one serial robot with adaptable passive exoskeletons is adequate to facilitate rehabilitation exercises.

@article{ansari_2019,
title = {Development and experimental investigation of a Quadrotor’s robust generalized dynamic inversion control system},
author = {Ansari, U., Bajodah, A.H.; Kada, B.},
journal = {Nonlinear Dynamics},
year = {2019},
institution = {King Abdulaziz University, Saudi Arabia},
abstract = {The development of a two-loops Quadrotor’s robust generalized dynamic inversion (RGDI)-based control system is presented. The outer (position) loop utilizes PD position control of the Quadrotor’s center of gravity (CG) in the three-dimensional inertial space, and it provides reference pitch and roll tilting angles commands to the inner loop, in addition to the thrust command that is required to track desired altitude trajectories. The inner (attitude) loop applies RGDI control of a prescribed asymptotically stable dynamics of tilting and attitude errors from reference-tilting and desired-attitude trajectories, and it provides the three required control torque values such that desired CG positions in instantaneous horizontal inertial planes and desired-attitude trajectories of the Quadrotor are tracked. The proposed closed loop system is shown to guarantee finite-time semi-global practically stable trajectory tracking. Numerical simulations of the proposed closed loop control system are performed on a six degrees of freedom Quadrotor’s mathematical model for nominal conditions and under parametric uncertainties and exogenous disturbances. Apart from numerical simulations, experimental tests are conducted on a three degrees of freedom Quadrotor test bench to assess performance of the RGDI control loop. Experimental results demonstrate improved tracking performance in comparison with classical Linear-Quadratic optimal control and conventional sliding mode control. },
issn = {0924-090X},
keywords = {Robust generalized dynamic inversion, Sliding mode control, Quadrotor control, Hover experimental test bench, Null control vector, Trajectory tracking, Finite-time stability, Semiglobal practical stability},
language = {English},
publisher = {Springer Nature}
}

The development of a two-loops Quadrotor’s robust generalized dynamic inversion (RGDI)-based control system is presented. The outer (position) loop utilizes PD position control of the Quadrotor’s center of gravity (CG) in the three-dimensional inertial space, and it provides reference pitch and roll tilting angles commands to the inner loop, in addition to the thrust command that is required to track desired altitude trajectories. The inner (attitude) loop applies RGDI control of a prescribed asymptotically stable dynamics of tilting and attitude errors from reference-tilting and desired-attitude trajectories, and it provides the three required control torque values such that desired CG positions in instantaneous horizontal inertial planes and desired-attitude trajectories of the Quadrotor are tracked. The proposed closed loop system is shown to guarantee finite-time semi-global practically stable trajectory tracking. Numerical simulations of the proposed closed loop control system are performed on a six degrees of freedom Quadrotor’s mathematical model for nominal conditions and under parametric uncertainties and exogenous disturbances. Apart from numerical simulations, experimental tests are conducted on a three degrees of freedom Quadrotor test bench to assess performance of the RGDI control loop. Experimental results demonstrate improved tracking performance in comparison with classical Linear-Quadratic optimal control and conventional sliding mode control.

@conference{gruenwald_2019,
title = {Direct Uncertainty Minimization in Model Reference Adaptive Control: Experimental Results},
author = {Gruenwald, B.C.; Yucelen, T.; Muse, J.A. },
booktitle = {AIAA Scitech 2019 Forum},
year = {2019},
institution = {University of South Florida; USA; Air Force Research Laboratory; USA},
abstract = {This paper presents an application of a recently developed direct uncertainty minimization approach for model reference adaptive control on a dual-rotor helicopter testbed. Specifically, the direct minimization approach uses a gradient minimization procedure to construct modification terms that are included in the adaptive control law and the update laws to improve the closed-loop system performance. These modification terms are activated when the system error between the uncertain dynamical system and a given reference model capturing the desired closed-loop dynamical system behavior is nonzero and then vanish as the system reaches steady-state. The experimental results in this paper demonstrate the capability of the direct minimization approach to improve the closed-loop system performance and enforce performance bounds. },
language = {English}
}

This paper presents an application of a recently developed direct uncertainty minimization approach for model reference adaptive control on a dual-rotor helicopter testbed. Specifically, the direct minimization approach uses a gradient minimization procedure to construct modification terms that are included in the adaptive control law and the update laws to improve the closed-loop system performance. These modification terms are activated when the system error between the uncertain dynamical system and a given reference model capturing the desired closed-loop dynamical system behavior is nonzero and then vanish as the system reaches steady-state. The experimental results in this paper demonstrate the capability of the direct minimization approach to improve the closed-loop system performance and enforce performance bounds.

@article{wu_2019,
title = {Discrete-Time Modified UDE-Based Current Control for LCL-Type Grid-Tied Inverters},
author = {Wu, Y.; Ye, Y.; Zhao, Q.; Cao, Y.; Xiong, Y.},
journal = {IEEE Transactions on Industrial Electronics},
year = {2019},
institution = {Zhongyuan University of Technology, China; Nanjing University of Aeronautics and Astronautics, China},
abstract = { In LCL-type grid tied inverters, the lumped disturbance, including parameter uncertainties, unmodeled dynamics, grid harmonics, will deteriorate the current tracking performance and lead to high total harmonic distortion (THD). The uncertainty and disturbance estimator (UDE) scheme provides an effective way to attenuate the lumped disturbance. However, UDE for the current control in LCL-type grid-tied inverters is far from perfection. In this paper, a discrete-time modified UDE (MUDE) scheme is proposed to improve the current tracking performance and robustness. In MUDE, a reduced-order model of the LCL filter combining with an active damping scheme is proposed. The stability performance is discussed in detail, and a rigorous stability condition is proposed in the first time. Moreover, the analysis of the controller sampling frequency and grid impedance, and their influences on the system stability is presented. A design case based on the stability condition is also given. Comparative experiments are conducted to verify the effectiveness of the proposed scheme. },
issn = {0278-0046 },
keywords = {Grid-tied inverter, LCL filter, uncertainty and disturbance estimator (UDE), stability analysis, total harmonic distortion (THD)},
language = {English},
publisher = {IEEE}
}

In LCL-type grid tied inverters, the lumped disturbance, including parameter uncertainties, unmodeled dynamics, grid harmonics, will deteriorate the current tracking performance and lead to high total harmonic distortion (THD). The uncertainty and disturbance estimator (UDE) scheme provides an effective way to attenuate the lumped disturbance. However, UDE for the current control in LCL-type grid-tied inverters is far from perfection. In this paper, a discrete-time modified UDE (MUDE) scheme is proposed to improve the current tracking performance and robustness. In MUDE, a reduced-order model of the LCL filter combining with an active damping scheme is proposed. The stability performance is discussed in detail, and a rigorous stability condition is proposed in the first time. Moreover, the analysis of the controller sampling frequency and grid impedance, and their influences on the system stability is presented. A design case based on the stability condition is also given. Comparative experiments are conducted to verify the effectiveness of the proposed scheme.

@article{li_2019,
title = {Distal-end force prediction of tendon-sheath mechanisms for flexible endoscopic surgical robots using deep learning},
author = {Li, X.; Cao, L.; Huat Tiong, A.M.; Phan, P.T.; Phee, S.J.},
journal = {Mechanism and Machine Theory},
year = {2019},
month = {04},
volume = {134},
institution = {Nanyang Technological University, Singapore},
abstract = {Accurate haptic feedback is highly challenging for flexible endoscopic surgical robots due to space limitation for sensors on small end-effectors and critical force hysteresis of their tendon-sheath mechanisms (TSMs). This paper proposes a deep learning approach to predicting the distal force of TSMs when manipulating a biological tissue based on only proximal-end measurements. Both Multilayer Perceptron (MLP) and Recurrent Neural Network (RNN) were investigated to study their capabilities of making sequential distal force predictions. The results were compared with those of the conventional modelling approach. It was observed that, when sufficient data was provided for training, RNN achieved the most accurate prediction (RMSE = 0.0219 N) in experiments with constant system velocity. The effects of insufficient training data, varying system velocity and irregular motion trajectories on the performance of RNN were further studied. Notably, RNN could precisely identify the current system phase in the force hysteresis profile and can be applied to TSMs with realistic non-periodic movement such as manual manipulation trajectory (RSME = 0.2287 N). The proposed approach can be applied to any TSM-driven robotic systems for accurate haptic feedback without requiring sensors at the distal ends of the robots. },
keywords = {Haptic feedback, Surgical robot, Tendon sheath mechanisms, Deep learning, Hysteresis},
language = {English},
publisher = {Elsevier Ltd.},
pages = {323-337}
}

Accurate haptic feedback is highly challenging for flexible endoscopic surgical robots due to space limitation for sensors on small end-effectors and critical force hysteresis of their tendon-sheath mechanisms (TSMs). This paper proposes a deep learning approach to predicting the distal force of TSMs when manipulating a biological tissue based on only proximal-end measurements. Both Multilayer Perceptron (MLP) and Recurrent Neural Network (RNN) were investigated to study their capabilities of making sequential distal force predictions. The results were compared with those of the conventional modelling approach. It was observed that, when sufficient data was provided for training, RNN achieved the most accurate prediction (RMSE = 0.0219 N) in experiments with constant system velocity. The effects of insufficient training data, varying system velocity and irregular motion trajectories on the performance of RNN were further studied. Notably, RNN could precisely identify the current system phase in the force hysteresis profile and can be applied to TSMs with realistic non-periodic movement such as manual manipulation trajectory (RSME = 0.2287 N). The proposed approach can be applied to any TSM-driven robotic systems for accurate haptic feedback without requiring sensors at the distal ends of the robots.

@article{chen_2019,
title = {Distributed fixed-time control under directed graph using input shaping},
author = {Chen, T.; Shan, J.},
journal = {Journal of the Franklin Institute},
year = {2019},
institution = {York University, Canada},
abstract = {This paper presents novel fixed-time controllers for the distributed tracking of multi-agent systems with double-integrator dynamics based on the input shaping technique under directed graphs. It is assumed that there is no cycle in the directed graph with a globally reachable leader. Distributed fixed-time controllers are designed for cases with various initial conditions by placing input shapers in all communication edges in the graph. Numerical simulations and experimental studies are conducted to verify the effectiveness of the proposed controllers. },
keywords = {Distributed control, Fixed-time control, Input shaping, Multi-agent systems, Directed graphs},
language = {English},
publisher = {Elsevier B.V.}
}

This paper presents novel fixed-time controllers for the distributed tracking of multi-agent systems with double-integrator dynamics based on the input shaping technique under directed graphs. It is assumed that there is no cycle in the directed graph with a globally reachable leader. Distributed fixed-time controllers are designed for cases with various initial conditions by placing input shapers in all communication edges in the graph. Numerical simulations and experimental studies are conducted to verify the effectiveness of the proposed controllers.

@article{tuhta_2019,
title = {Dynamic Analysis of Model Steel Structures Retrofitted with GFRP Composites under Microtremor Vibration},
author = {Tuhta, S.; Gunday, F.; Aydin, H.},
journal = {International Journal of Trend in Scientific Research and Development},
year = {2019},
volume = {3},
number = {2},
institution = {Ondokuz Mayis University, Turkey},
abstract = {There are many varieties of the structural and architectural structures strengthened with different FRP composites are gaining popularity, and there is a growing need to understand and compare the behavior of these structures before-after GFRP composite strengthening. In this study, model steel structure was tested on the bench-scale earthquake simulator (The Quanser Shake Table) using ambient vibration, to determine the dynamic response. After this, slabs of the model steel structure was strengthened with GFRP composite, and tested on the bench-scale earthquake simulator (The Quanser Shake Table) using ambient vibration, to determine the dynamic behavior. Finally, dynamic responses of model steel structure before and after GFRP composite strengthening, such as displacements and maximum-minimum acceleration, were compared. At the end of the study, it is seen that displacements had decreased along the height of the model steel structure. Also, it is seen from the earthquake analyses that GFRP strengthening is very effective on the dynamic responses of the model steel structure. },
issn = {2456 - 6470},
keywords = {Dynamic Analysis; GFRP; Microtremor Vibration; Shake Table},
language = {English}
}

There are many varieties of the structural and architectural structures strengthened with different FRP composites are gaining popularity, and there is a growing need to understand and compare the behavior of these structures before-after GFRP composite strengthening. In this study, model steel structure was tested on the bench-scale earthquake simulator (The Quanser Shake Table) using ambient vibration, to determine the dynamic response. After this, slabs of the model steel structure was strengthened with GFRP composite, and tested on the bench-scale earthquake simulator (The Quanser Shake Table) using ambient vibration, to determine the dynamic behavior. Finally, dynamic responses of model steel structure before and after GFRP composite strengthening, such as displacements and maximum-minimum acceleration, were compared. At the end of the study, it is seen that displacements had decreased along the height of the model steel structure. Also, it is seen from the earthquake analyses that GFRP strengthening is very effective on the dynamic responses of the model steel structure.

@article{lee_2019,
title = {Enhancement of Energy-Based Swing-Up Controller via Entropy Search},
author = {Lee, C.S.; Chang, D.E.},
year = {2019},
institution = {KAIST, Korea},
abstract = {An energy based approach for stabilizing a mechanical system has offered a simple yet powerful control scheme. However, since it does not impose such strong constraints on parameter space of the controller, finding appropriate parameter values for an optimal controller is known to be hard. This paper intends to generate an optimal energy-based controller for swinging up a rotary inverted pendulum, also known as the Furuta pendulum, by applying the Bayesian optimization called Entropy Search. Simulations and experiments show that the optimal controller has an improved performance compared to a nominal controller for various initial conditions. },
language = {English}
}

An energy based approach for stabilizing a mechanical system has offered a simple yet powerful control scheme. However, since it does not impose such strong constraints on parameter space of the controller, finding appropriate parameter values for an optimal controller is known to be hard. This paper intends to generate an optimal energy-based controller for swinging up a rotary inverted pendulum, also known as the Furuta pendulum, by applying the Bayesian optimization called Entropy Search. Simulations and experiments show that the optimal controller has an improved performance compared to a nominal controller for various initial conditions.

@article{schleer_2019,
title = {Evaluation of Different Modes of Haptic Guidance for Robotic Surgery},
author = {Schleer, P.; Drobinsky, S.; Radermacher, K.},
journal = {IFAC-PapersOnLine},
year = {2019},
volume = {51},
number = {34},
institution = {RWTH Aachen University, Germany},
abstract = {The evolution of surgery has resulted in a plethora of systems varying in their application field, size, as well as degree of autonomy. Especially systems which combine principles of so-called synergistic robotic systems and master-slave-telemanipulators are interesting concerning cooperative aspects of surgeon and robotic system. While the former provide haptic guidance information (“virtual fixtures”), the latter provide haptic feedback from position or force sensor information of the slave device. During the design of these combined systems particular attention has to be paid during the allocation of information to the haptic information channel as superimposing of haptic guidance information and haptic sensor feedback can lead to concealment of essential feedback information. This paper reports on an experimental usability evaluation of different haptic guidance modes varying in their degree of autonomy as well as degree of freedom (DOF) with respect to three surgical scenarios, namely reaching a predefined position and orientation, tracking a predefined 3D trajectory, and applying a defined force (such as during e.g. a 3D-bone milling task). The goal was to evaluate whether some DOF of haptic guidance information can be left free for force sensor information feedback. General findings indicate that haptic guidance does not have to be augmented on three DOF to improve usability. Therefore, a combination of haptic sensor information feedback and haptic guidance information divided between individual DOF seems to be a potential solution. },
keywords = {Robotics, Telerobotics, Telemanipulation, Robotic manipulators, Robotic surgery, Robot navigation, Trajectories, Shared Control, Guidance systems, Haptics},
language = {English},
publisher = {Elsevier Ltd.}
}

The evolution of surgery has resulted in a plethora of systems varying in their application field, size, as well as degree of autonomy. Especially systems which combine principles of so-called synergistic robotic systems and master-slave-telemanipulators are interesting concerning cooperative aspects of surgeon and robotic system. While the former provide haptic guidance information (“virtual fixtures”), the latter provide haptic feedback from position or force sensor information of the slave device. During the design of these combined systems particular attention has to be paid during the allocation of information to the haptic information channel as superimposing of haptic guidance information and haptic sensor feedback can lead to concealment of essential feedback information. This paper reports on an experimental usability evaluation of different haptic guidance modes varying in their degree of autonomy as well as degree of freedom (DOF) with respect to three surgical scenarios, namely reaching a predefined position and orientation, tracking a predefined 3D trajectory, and applying a defined force (such as during e.g. a 3D-bone milling task). The goal was to evaluate whether some DOF of haptic guidance information can be left free for force sensor information feedback. General findings indicate that haptic guidance does not have to be augmented on three DOF to improve usability. Therefore, a combination of haptic sensor information feedback and haptic guidance information divided between individual DOF seems to be a potential solution.

@article{gonzalez_2019,
title = {Event-triggered predictor-based control with gain-Scheduling and extended state observer for networked control systems},
author = {González, A.; Cuenca, A.; Balaguer, V.; García, P.},
journal = {Information Sciences},
year = {2019},
month = {07},
volume = {491},
institution = {Universidad de Zaragoza, Spain; Universitat Politècnica de València, Spain},
abstract = {This paper investigates the stabilization of Networked Control Systems (NCS) with mismatched disturbances through a novel Event-Triggered Control (ETC), composed of a predictor-feedback scheme and a gain-scheduled Extended State Observer (ESO). The key idea of the proposed control strategy is threefold: (i) to reduce resource usage in the NCS (bandwidth, energy) while maintaining a satisfactory control performance; (ii) to counteract the main negative effects of NCS: time-varying delays, packet dropouts, packet disorder, and (iii) to reject the steady-state error in the controlled output due to mismatched disturbances. Moreover, we address the co-design of the controller/observer gains, together with the event-triggered parameters, by means of Linear Matrix Inequalities (LMI) and Cone Complementarity Linearization (CCL) approaches. Finally, we illustrate the effectiveness of the proposed control synthesis by simulation and experimental results in a Unmanned Aerial Vehicle (UAV) based test-bed platform.This paper investigates the stabilization of Networked Control Systems (NCS) with mismatched disturbances through a novel Event-Triggered Control (ETC), composed of a predictor-feedback scheme and a gain-scheduled Extended State Observer (ESO). The key idea of the proposed control strategy is threefold: (i) to reduce resource usage in the NCS (bandwidth, energy) while maintaining a satisfactory control performance; (ii) to counteract the main negative effects of NCS: time-varying delays, packet dropouts, packet disorder, and (iii) to reject the steady-state error in the controlled output due to mismatched disturbances. Moreover, we address the co-design of the controller/observer gains, together with the event-triggered parameters, by means of Linear Matrix Inequalities (LMI) and Cone Complementarity Linearization (CCL) approaches. Finally, we illustrate the effectiveness of the proposed control synthesis by simulation and experimental results in a Unmanned Aerial Vehicle (UAV) based test-bed platform. },
keywords = {Time-varying delay, Networked control system, Packet disorder, Packet loss, Predictor-based control, Gain-scheduling, ESO},
language = {English},
publisher = {Elsevier B.V.},
pages = {90-108}
}

This paper investigates the stabilization of Networked Control Systems (NCS) with mismatched disturbances through a novel Event-Triggered Control (ETC), composed of a predictor-feedback scheme and a gain-scheduled Extended State Observer (ESO). The key idea of the proposed control strategy is threefold: (i) to reduce resource usage in the NCS (bandwidth, energy) while maintaining a satisfactory control performance; (ii) to counteract the main negative effects of NCS: time-varying delays, packet dropouts, packet disorder, and (iii) to reject the steady-state error in the controlled output due to mismatched disturbances. Moreover, we address the co-design of the controller/observer gains, together with the event-triggered parameters, by means of Linear Matrix Inequalities (LMI) and Cone Complementarity Linearization (CCL) approaches. Finally, we illustrate the effectiveness of the proposed control synthesis by simulation and experimental results in a Unmanned Aerial Vehicle (UAV) based test-bed platform.This paper investigates the stabilization of Networked Control Systems (NCS) with mismatched disturbances through a novel Event-Triggered Control (ETC), composed of a predictor-feedback scheme and a gain-scheduled Extended State Observer (ESO). The key idea of the proposed control strategy is threefold: (i) to reduce resource usage in the NCS (bandwidth, energy) while maintaining a satisfactory control performance; (ii) to counteract the main negative effects of NCS: time-varying delays, packet dropouts, packet disorder, and (iii) to reject the steady-state error in the controlled output due to mismatched disturbances. Moreover, we address the co-design of the controller/observer gains, together with the event-triggered parameters, by means of Linear Matrix Inequalities (LMI) and Cone Complementarity Linearization (CCL) approaches. Finally, we illustrate the effectiveness of the proposed control synthesis by simulation and experimental results in a Unmanned Aerial Vehicle (UAV) based test-bed platform.

@article{penaloza-mejia_2019,
title = {Evolving behaviors for bounded-flow tracking control of second-order dynamical systems},
author = {Peñaloza-Mejía, O.; Clemente, E.; Meza-Sánchez, M.; Pérez, C.B.},
journal = {Engineering Applications of Artificial Intelligence},
year = {2019},
volume = {78},
institution = {Instituto Tecnológico de Sonora, Mexico; Tecnológico Nacional de México, Mexico},
abstract = {A two-stage methodology for the development of nonlinear analytical controllers for tracking control in second-order dynamical systems subject to flow variable constraints is proposed. It extends the concepts of behavior-based control to describe the system as the summation of its unforced, forced, and learned behaviors. While the unforced behavior is characterized by its analytical dynamical model, the forced and learned behaviors are introduced in the system by means of a Control-Theory-based controller and an evolutionary learning process based in the Genetic Programming paradigm. The integration of both approaches in a unified framework allows the system to exhibit a good tracking performance while keeping the flow variable bounded to a desired value, parametrized as a boundary interval. A set of 180993 learned behaviors, which preserves asymptotic convergence to the desired behavior while achieving a bounded flow variable, were discovered by the evolutionary process. Simulation results show the effectiveness of the found nonlinear tracking controllers with the highest fitness value, as well as the one with the lower structural complexity. A performance comparison between numerical simulations and real-time experiments for a mechatronic prototype is also provided to illustrate the feasibility of the proposed method in real-world applications. },
keywords = {Behaviors, Genetic programming, Second-order dynamical systems, Nonlinear tracking control, Bounded flow variable},
language = {English},
publisher = {Elsevier Ltd.},
pages = {12-27}
}

A two-stage methodology for the development of nonlinear analytical controllers for tracking control in second-order dynamical systems subject to flow variable constraints is proposed. It extends the concepts of behavior-based control to describe the system as the summation of its unforced, forced, and learned behaviors. While the unforced behavior is characterized by its analytical dynamical model, the forced and learned behaviors are introduced in the system by means of a Control-Theory-based controller and an evolutionary learning process based in the Genetic Programming paradigm. The integration of both approaches in a unified framework allows the system to exhibit a good tracking performance while keeping the flow variable bounded to a desired value, parametrized as a boundary interval. A set of 180993 learned behaviors, which preserves asymptotic convergence to the desired behavior while achieving a bounded flow variable, were discovered by the evolutionary process. Simulation results show the effectiveness of the found nonlinear tracking controllers with the highest fitness value, as well as the one with the lower structural complexity. A performance comparison between numerical simulations and real-time experiments for a mechatronic prototype is also provided to illustrate the feasibility of the proposed method in real-world applications.

@conference{dogan_2019,
title = {Experimental Results of a Model Reference Adaptive Control Law on an Uncertain System with Unmodeled Dynamics},
author = {Dogan, K.M.; Yucelen, T.; Yildirim, E.; Muse, J.A.},
booktitle = {AIAA Scitech 2019 Forum},
year = {2019},
institution = {University of South Florida, FL, USA},
abstract = {Model reference adaptive control is a powerful tool that has a capability to suppress the effect of system uncertainties for achieving a desired level of closed-loop system performance. Yet, for a wide array of applications including unmodeled dynamics such as coupled rigid body systems with flexible interconnection links, airplanes with high aspect ratio wings, and high speed vehicles with strong rigid body and flexible dynamics coupling, the closed-loop system stability with model reference adaptive control laws can be challenged. To this end, the authors have recently studied the stability interplay between a class of unmodeled dynamics and system uncertainties for model reference adaptive control laws, and proposed a robustifying term to relax the resulting interplay. The contribution of this paper is to present experimental results for the purpose of demonstrating the efficacy of this proposed term, where we use a benchmark mechanical system setup involving an inverted pendulum on a cart coupled with another cart through a spring in the presence of unknown frictions. },
publisher = {AIAA}
}

Model reference adaptive control is a powerful tool that has a capability to suppress the effect of system uncertainties for achieving a desired level of closed-loop system performance. Yet, for a wide array of applications including unmodeled dynamics such as coupled rigid body systems with flexible interconnection links, airplanes with high aspect ratio wings, and high speed vehicles with strong rigid body and flexible dynamics coupling, the closed-loop system stability with model reference adaptive control laws can be challenged. To this end, the authors have recently studied the stability interplay between a class of unmodeled dynamics and system uncertainties for model reference adaptive control laws, and proposed a robustifying term to relax the resulting interplay. The contribution of this paper is to present experimental results for the purpose of demonstrating the efficacy of this proposed term, where we use a benchmark mechanical system setup involving an inverted pendulum on a cart coupled with another cart through a spring in the presence of unknown frictions.

@conference{arabi_2019,
title = {Experimental Results with the Set-Theoretic Model Reference Adaptive Control Architecture on an Aerospace Testbed},
author = {Arabi, E.; Yucelen, T.},
booktitle = {AIAA Scitech 2019 Forum},
year = {2019},
institution = {University of South Florida, FL, USA},
abstract = {In this paper, we present experimental results of a recently developed set-theoretic model reference adaptive control architecture on an aerospace testbed, which is configured as a conventional dual-rotor helicopter. The key feature of this architecture allows the system error bound between the state of an uncertain dynamical system and the state of a reference model, which captures a desired closed-loop system performance, to be less than a-priori, user-defined worst-case performance bound. This means that this proposed architecture is suitable for enforcing strict performance guarantees during the transient and steady-state response of the adaptation process. Specifically, we first experimentally demonstrate the practical capabilities of this adaptive control algorithm with constant performance bounds on the considered testbed. We then consider the time-varying performance bounds, where we highlight how a control designer is empowered by the set-theoretic model reference adaptive control architecture to control the closed-loop system performance as desired on different time intervals (e.g. transient time interval and steady-state time interval) and also how to handle a possible system initialization error that can happen in practice. },
language = {English},
publisher = {AIAA}
}

In this paper, we present experimental results of a recently developed set-theoretic model reference adaptive control architecture on an aerospace testbed, which is configured as a conventional dual-rotor helicopter. The key feature of this architecture allows the system error bound between the state of an uncertain dynamical system and the state of a reference model, which captures a desired closed-loop system performance, to be less than a-priori, user-defined worst-case performance bound. This means that this proposed architecture is suitable for enforcing strict performance guarantees during the transient and steady-state response of the adaptation process. Specifically, we first experimentally demonstrate the practical capabilities of this adaptive control algorithm with constant performance bounds on the considered testbed. We then consider the time-varying performance bounds, where we highlight how a control designer is empowered by the set-theoretic model reference adaptive control architecture to control the closed-loop system performance as desired on different time intervals (e.g. transient time interval and steady-state time interval) and also how to handle a possible system initialization error that can happen in practice.

@article{jiang2_2019,
title = {Extraction of structural modal information using acoustic sensor measurements and machine learning},
author = {Jiang, Z.; Zhang, Z.; Maxwell, A.},
journal = {Journal of Sound and Vibration},
year = {2019},
month = {06},
volume = {450},
institution = {San Francisco State University, USA; Western Digital Corporation, USA},
abstract = {Natural hazards could be very destructive. One challenge that society faces is how to rapidly, accurately and economically evaluate the damage of structures in the aftermath of a disaster. To overcome the limitations of visual inspections, a large body of research has focused on the design and deployment of the structural health monitoring systems, in which various sensors are deployed to obtain the necessary data for the specific health monitoring schemes. These sensors are typically installed with wired and/or wireless networks which the deployment and operation cost are obstacles to their usage. In this study, a novel systematic methodology, consisting of advanced cascading signal pre-processing techniques and a feature extraction method derived from machine learning, is proposed to identify low-frequency modal properties of structures using small amount of infrasound measurements obtained from microphones. In addition to providing the theoretical proofs, experiments on a vibrating structure subjected to ground excitations are conducted to verify the effectiveness and robustness of the proposed methodology. The study confirmed the feasibility of using microphone measurements as a means to perform non-contact and non-destructive structural health monitoring evaluation. To further investigate the effects of the several important factors, namely signal-to-noise ratio, number of reference sensors and the amount of collected data, a parametric study is performed to quantify their influences on the accuracy of identifying the desired modal property. },
keywords = {Non-contact, Non-destructive, Structural health monitoring, Infrasound microphone measurement, Machine learning, Feature extraction, Neural network},
language = {English},
publisher = {Elsevier B.V.},
pages = {156-174}
}

Natural hazards could be very destructive. One challenge that society faces is how to rapidly, accurately and economically evaluate the damage of structures in the aftermath of a disaster. To overcome the limitations of visual inspections, a large body of research has focused on the design and deployment of the structural health monitoring systems, in which various sensors are deployed to obtain the necessary data for the specific health monitoring schemes. These sensors are typically installed with wired and/or wireless networks which the deployment and operation cost are obstacles to their usage. In this study, a novel systematic methodology, consisting of advanced cascading signal pre-processing techniques and a feature extraction method derived from machine learning, is proposed to identify low-frequency modal properties of structures using small amount of infrasound measurements obtained from microphones. In addition to providing the theoretical proofs, experiments on a vibrating structure subjected to ground excitations are conducted to verify the effectiveness and robustness of the proposed methodology. The study confirmed the feasibility of using microphone measurements as a means to perform non-contact and non-destructive structural health monitoring evaluation. To further investigate the effects of the several important factors, namely signal-to-noise ratio, number of reference sensors and the amount of collected data, a parametric study is performed to quantify their influences on the accuracy of identifying the desired modal property.

@article{zhu_2019,
title = {Fluidic Fabric Muscle Sheets for Wearable and Soft Robotics},
author = {Zhu, M.; Nho Do, T.; Hawkes, E.; Visell, Y.},
year = {2019},
institution = {University of California, Santa Barbara, USA; University of New South Wales, Australia},
abstract = {Conformable robotic systems are attractive for applications in which they can be used to actuate structures with large surface areas, to provide forces through wearable garments, or to realize autonomous robotic systems. We present a new family of soft actuators that we refer to as Fluidic Fabric Muscle Sheets (FFMS). They are composite fabric structures that integrate fluidic transmissions based on arrays of elastic tubes. These sheet-like actuators can strain, squeeze, bend, and conform to hard or soft objects of arbitrary shapes or sizes, including the human body. We show how to design and fabricate FFMS actuators via facile apparel engineering methods, including computerized sewing techniques. Together, these determine the distributions of stresses and strains that can be generated by the FFMS. We present a simple mathematical model that proves effective for predicting their performance. FFMS can operate at frequencies of 5 Hertz or more, achieve engineering strains exceeding 100%, and exert forces greater than 115 times their own weight. They can be safely used in intimate contact with the human body even when delivering stresses exceeding 106 Pascals. We demonstrate their versatility for actuating a variety of bodies or structures, and in configurations that perform multi-axis actuation, including bending and shape change. As we also show, FFMS can be used to exert forces on body tissues for wearable and biomedical applications. We demonstrate several potential use cases, including a miniature steerable robot, a glove for grasp assistance, garments for applying compression to the extremities, and devices for actuating small body regions or tissues via localized skin stretch. },
keywords = {Artificial muscles, Sheet-like actuators, Fluidic actuation, Wearables, Fabric, Textiles},
language = {English}
}

Conformable robotic systems are attractive for applications in which they can be used to actuate structures with large surface areas, to provide forces through wearable garments, or to realize autonomous robotic systems. We present a new family of soft actuators that we refer to as Fluidic Fabric Muscle Sheets (FFMS). They are composite fabric structures that integrate fluidic transmissions based on arrays of elastic tubes. These sheet-like actuators can strain, squeeze, bend, and conform to hard or soft objects of arbitrary shapes or sizes, including the human body. We show how to design and fabricate FFMS actuators via facile apparel engineering methods, including computerized sewing techniques. Together, these determine the distributions of stresses and strains that can be generated by the FFMS. We present a simple mathematical model that proves effective for predicting their performance. FFMS can operate at frequencies of 5 Hertz or more, achieve engineering strains exceeding 100%, and exert forces greater than 115 times their own weight. They can be safely used in intimate contact with the human body even when delivering stresses exceeding 106 Pascals. We demonstrate their versatility for actuating a variety of bodies or structures, and in configurations that perform multi-axis actuation, including bending and shape change. As we also show, FFMS can be used to exert forces on body tissues for wearable and biomedical applications. We demonstrate several potential use cases, including a miniature steerable robot, a glove for grasp assistance, garments for applying compression to the extremities, and devices for actuating small body regions or tissues via localized skin stretch.

@article{nath_2019,
title = {Fuzzy tuned model based control for level and temperature processes},
author = {Manikya Nath, U.; Dey,, C.; Mudi, R.K.},
journal = {Microsystem Technologies},
year = {2019},
month = {03},
volume = {25},
number = {3},
institution = {Jadavpur University, India; University of Calcutta, India},
abstract = {At present, model based controllers are being extensively used in process industries due to their simple tuning strategy. Internal model control (IMC) is one of the widely accepted model based controller design methodologies in close-loop control applications with considerable process lag. But, similar to the other model based controller design techniques, availability of an appropriate linear model of the concerned process is essential for IMC design. However, in reality, most of the industrial processes are nonlinear in nature. Hence, designing of an IMC controller for such cases is truly a difficult task especially for ensuring satisfactory performance during transient as well as steady state operating conditions simultaneously. In this study, to achieve an overall acceptable process response, we propose an auto-tuning scheme for the conventional IMC-PID controller by varying its sole tuning parameter depending on the latest process operating conditions. Superiority of the proposed auto-tuned IMC-PID controller is observed for real-time level and temperature processes where the close-loop time constant (λ) is varied with the help of twenty-five fuzzy rules defined on the values of process error (e) and change of error (Δe). },
language = {English},
publisher = {Springer Nature Switzerland}
}

At present, model based controllers are being extensively used in process industries due to their simple tuning strategy. Internal model control (IMC) is one of the widely accepted model based controller design methodologies in close-loop control applications with considerable process lag. But, similar to the other model based controller design techniques, availability of an appropriate linear model of the concerned process is essential for IMC design. However, in reality, most of the industrial processes are nonlinear in nature. Hence, designing of an IMC controller for such cases is truly a difficult task especially for ensuring satisfactory performance during transient as well as steady state operating conditions simultaneously. In this study, to achieve an overall acceptable process response, we propose an auto-tuning scheme for the conventional IMC-PID controller by varying its sole tuning parameter depending on the latest process operating conditions. Superiority of the proposed auto-tuned IMC-PID controller is observed for real-time level and temperature processes where the close-loop time constant (λ) is varied with the help of twenty-five fuzzy rules defined on the values of process error (e) and change of error (Δe).

@conference{chen3_2019,
title = {Gaussian Processes Model-Based Control of Underactuated Balance Robots},
author = {Chen, K.; Yi, J.; Song, D.},
booktitle = {2019 IEEE International Conference on Robotics and Automation (ICRA)},
year = {2019},
institution = {Rutgers University, USA; Texas A&M University, College Station, USA},
abstract = {Control of underactuated balance robot requires external subsystem trajectory tracking and internal unstable subsystem balancing with limited control authority. We present a learning-based control approach for underactuated balance robots. The tracking and balancing control is designed the controller in fast- and slow-time scales. In the slow-time scale, model predictive control is adopted to plan desired internal state profile to achieve external trajectory tracking task. The internal state is then stabilized around the planned profile in the fast-time scale. The control design is based on a learned Gaussian process (GP) regression model without need of apriori knowledge about the robot dynamics. The controller also incorporates the GP model predicted variance to enhance robustness to modeling errors. Experiments are presented using a Furuta pendulum system. },
language = {English},
publisher = {IEEE}
}

Control of underactuated balance robot requires external subsystem trajectory tracking and internal unstable subsystem balancing with limited control authority. We present a learning-based control approach for underactuated balance robots. The tracking and balancing control is designed the controller in fast- and slow-time scales. In the slow-time scale, model predictive control is adopted to plan desired internal state profile to achieve external trajectory tracking task. The internal state is then stabilized around the planned profile in the fast-time scale. The control design is based on a learned Gaussian process (GP) regression model without need of apriori knowledge about the robot dynamics. The controller also incorporates the GP model predicted variance to enhance robustness to modeling errors. Experiments are presented using a Furuta pendulum system.

@article{de-loza_2019,
title = {High‐order sliding‐mode observer–based input‐output linearization},
author = {Ferreira de Loza, A.; Fridman, L.; Aguilar, L.T., Iriarte, R.},
journal = {International Journal of Robust and Nonlinear Control},
year = {2019},
institution = {Instituto Politécnico Nacional-CITEDI, Mexico; Universidad Nacional Autónoma de México, Mexico},
abstract = {The problem of output control in multiple‐input–multiple‐output nonlinear systems is addressed. A high‐order sliding‐mode observer is used to estimate the states of the system and identify the discrepancy between the nominal model and the real plant. The exact and finite‐time estimation may be tackled as long as the system presents the algebraic strong observability property. Thus, a continuous robust input‐output linearization strategy can be obtained with respect to a prescribed output. As a consequence, the closed‐loop dynamics performs robustly to uncertainties/perturbations. To illustrate the advantages of the proposed method, we introduce a study case that demands a robust linear system behavior: the self‐oscillations induced in an underactuated mechanical system through a two‐relay controller. Experiments with an inertial wheel pendulum illustrate the feasibility of the proposed approach. },
keywords = {robust nonlinear control, uncertain systems, disturbance identification, sliding mode control},
language = {English},
publisher = {John Wiley & Sons, Ltd.}
}

The problem of output control in multiple‐input–multiple‐output nonlinear systems is addressed. A high‐order sliding‐mode observer is used to estimate the states of the system and identify the discrepancy between the nominal model and the real plant. The exact and finite‐time estimation may be tackled as long as the system presents the algebraic strong observability property. Thus, a continuous robust input‐output linearization strategy can be obtained with respect to a prescribed output. As a consequence, the closed‐loop dynamics performs robustly to uncertainties/perturbations. To illustrate the advantages of the proposed method, we introduce a study case that demands a robust linear system behavior: the self‐oscillations induced in an underactuated mechanical system through a two‐relay controller. Experiments with an inertial wheel pendulum illustrate the feasibility of the proposed approach.

@article{tran_2019,
title = {Implementing Homomorphic Encryption Based Secure Feedback Control for Physical Systems},
author = {Tran, .; Farokhi, F.; Cantoni, M.; Shames, I.},
year = {2019},
institution = {University of Melbourne, Australia},
abstract = {This paper is about an encryption based approach to the secure implementation of feedback controllers for physical systems. Specifically, Paillier's homomorphic encryption is used in a custom digital implementation of a class of linear dynamic controllers, including static gain as a special case. The implementation is amenable to Field Programmable Gate Array (FPGA) realization. Experimental results, including timing analysis and resource usage characteristics for different encryption key lengths, are presented for the realization of a controller for an inverted pendulum; as this is an unstable plant, the control is necessarily fast. },
keywords = {secure control, homomorphic encryption, Paillier encryption, digital design, FPGA},
language = {English}
}

This paper is about an encryption based approach to the secure implementation of feedback controllers for physical systems. Specifically, Paillier's homomorphic encryption is used in a custom digital implementation of a class of linear dynamic controllers, including static gain as a special case. The implementation is amenable to Field Programmable Gate Array (FPGA) realization. Experimental results, including timing analysis and resource usage characteristics for different encryption key lengths, are presented for the realization of a controller for an inverted pendulum; as this is an unstable plant, the control is necessarily fast.

@article{ocampo_2019,
title = {Improving User Performance in Haptics-Based Rehabilitation Exercises by Colocation of User’s Visual and Motor Axes via a Three-Dimensional Augmented-Reality Display},
author = {Ocampo, R.; Tavakoli, M.},
journal = {IEEE Robotics and Automation Letters},
year = {2019},
volume = {3},
number = {4},
institution = {University of Alberta, Canada},
abstract = {Serious games are recently becoming a common sight in rehabilitation settings to provide motivation for patients undergoing therapy to regain upper limb function after disability. These are often presented using a 2D monitor to the patient who uses a robotic device (haptic user interface) as the game controller. In this paper, we develop a 3D spatial Augmented Reality (AR) display to colocate visual and haptic feedback to the user in three rehabilitative games. The same games are also displayed in a 2D non-immersive Virtual Reality (VR) and are compared against their AR counterpart in terms of user task performance to evaluate the benefit of the 3D AR system. To simulate a rehabilitation scenario, able-bodied participants are put under cognitive load (CL) for simulating disability-induced cognitive deficiencies when performing the tasks. A within-subjects analysis of 10 participants was carried out for the rehabilitative games. The results show that AR leads to the best user performance with or without cognitive loading. This result is most evident in dynamic exercises where the participants are required to have quick reaction times and fast movement. Furthermore, even while AR had a significant difference over VR, one of the tasks showed that performance in AR between non-CL and CL cases were similar, thereby showing how AR can alleviate the negative effects of CL. },
keywords = {Virtual Reality and Interfaces, Haptics and Haptic Interfaces, Rehabilitation Robotics},
language = {English},
publisher = {IEEE}
}

Serious games are recently becoming a common sight in rehabilitation settings to provide motivation for patients undergoing therapy to regain upper limb function after disability. These are often presented using a 2D monitor to the patient who uses a robotic device (haptic user interface) as the game controller. In this paper, we develop a 3D spatial Augmented Reality (AR) display to colocate visual and haptic feedback to the user in three rehabilitative games. The same games are also displayed in a 2D non-immersive Virtual Reality (VR) and are compared against their AR counterpart in terms of user task performance to evaluate the benefit of the 3D AR system. To simulate a rehabilitation scenario, able-bodied participants are put under cognitive load (CL) for simulating disability-induced cognitive deficiencies when performing the tasks. A within-subjects analysis of 10 participants was carried out for the rehabilitative games. The results show that AR leads to the best user performance with or without cognitive loading. This result is most evident in dynamic exercises where the participants are required to have quick reaction times and fast movement. Furthermore, even while AR had a significant difference over VR, one of the tasks showed that performance in AR between non-CL and CL cases were similar, thereby showing how AR can alleviate the negative effects of CL.

@article{xin_2019,
title = {Input-output tracking control of a 2-DOF laboratory helicopter with improved algebraic differential estimation},
author = {Xin, Y.; Qin, Z.-C.; Sun, J.-Q.},
journal = {Mechanical Systems and Signal Processing},
year = {2019},
month = {02},
volume = {116},
institution = {Tianjin University, China; Shandong University of Technology, China; University of California, Merced, USA},
abstract = {This paper presents a study on input-output feedback linearization control (OFLC) of a laboratory twin rotor helicopter system based on an improved algebraic differential estimation approach. In the previous algebraic differential estimation studies, the reset time T(r) is always selected cautiously in a narrow range because the estimation accuracy is very sensitive to T(r). Too small or too large T(r) reset time will lead to an inaccurate estimation of signal derivatives. In this paper, we first propose a new resetting and overlapping strategy for improving the robustness of the estimation algorithm. Then it is used to estimate the velocities of pitch and yaw motions. The OFLC is designed and verified by letting the output signals track different periodic reference signals. Both simulation and experimental results show better control performance as compared with the LQR design. },
keywords = {Output feedback linearization control (OFLC), Algebraic differential estimation, Trajectory tracking 2-DOF helicopter},
language = {English},
publisher = {Elsevier Ltd.},
pages = {843-857}
}

This paper presents a study on input-output feedback linearization control (OFLC) of a laboratory twin rotor helicopter system based on an improved algebraic differential estimation approach. In the previous algebraic differential estimation studies, the reset time T(r) is always selected cautiously in a narrow range because the estimation accuracy is very sensitive to T(r). Too small or too large T(r) reset time will lead to an inaccurate estimation of signal derivatives. In this paper, we first propose a new resetting and overlapping strategy for improving the robustness of the estimation algorithm. Then it is used to estimate the velocities of pitch and yaw motions. The OFLC is designed and verified by letting the output signals track different periodic reference signals. Both simulation and experimental results show better control performance as compared with the LQR design.

@article{volpp_2019,
title = {Meta-Learning Acquisition Functions for Bayesian Optimization},
author = {Volpp, M.; Frohlich, L.; Doerr, A.; Hutter, F.; Daniel, C.},
year = {2019},
institution = {Bosch Center for Artificial Intelligence, Germany; Max Planck Institute for Intelligent Systems, Germany; University of Freiburg; Germany },
abstract = {Many practical applications of machine learning require data-efficient black-box function optimization, e.g., to identify hyperparameters or process settings. However, readily available algorithms are typically designed to be universal optimizers and are, thus, often suboptimal for specific tasks. We therefore propose a method to learn optimizers which are automatically adapted to a given class of objective functions, e.g., in the context of sim-to-real applications. Instead of learning optimization from scratch, the proposed approach is firmly based within the famous Bayesian optimization framework. Only the acquisition function (AF) is replaced by a learned neural network and therefore the resulting algorithm is still able to exploit the proven generalization capabilities of Gaussian processes. We present experiments on several simulated as well as on a sim-to-real transfer task. The results show that the learned optimizers (1) consistently perform better than or on-par with known AFs on general function classes and (2) can automatically identify structural properties of a function class using cheap simulations and transfer this knowledge to adapt rapidly to real hardware tasks, thereby significantly outperforming existing problem-agnostic AFs. },
language = {English}
}

Many practical applications of machine learning require data-efficient black-box function optimization, e.g., to identify hyperparameters or process settings. However, readily available algorithms are typically designed to be universal optimizers and are, thus, often suboptimal for specific tasks. We therefore propose a method to learn optimizers which are automatically adapted to a given class of objective functions, e.g., in the context of sim-to-real applications. Instead of learning optimization from scratch, the proposed approach is firmly based within the famous Bayesian optimization framework. Only the acquisition function (AF) is replaced by a learned neural network and therefore the resulting algorithm is still able to exploit the proven generalization capabilities of Gaussian processes. We present experiments on several simulated as well as on a sim-to-real transfer task. The results show that the learned optimizers (1) consistently perform better than or on-par with known AFs on general function classes and (2) can automatically identify structural properties of a function class using cheap simulations and transfer this knowledge to adapt rapidly to real hardware tasks, thereby significantly outperforming existing problem-agnostic AFs.

@article{qin_2019,
title = {Multi‐objective optimal motion control of a laboratory helicopter based on parallel simple cell mapping method},
author = {Qin, Z.-C.; Xin, Y.; Sun, J.-Q.},
journal = {Asian Journal of Control},
year = {2019},
institution = {Shandong University of Technology, China; Tianjin University, China; University of California, Merced, USA},
abstract = {This paper presents a study of multi‐objective optimal design of nonlinear control systems and has validated the control design with a twin rotor model helicopter. The gains of the porportional integral differential (PID) control are designed in the framework of multi‐objective opitmization. Eight design paramaters are optimized to minimize six time‐domain objective objective functions. The study of multi‐objective optimal design of feedback control with such a number of design paramaters and objective functions is rare in the literature. The Pareto optimal solutions are obtained by the proposed parallel simple cell mapping method consisting of a robust Pareto set recovery algorithm and a rolling subdivision technique. The proposed parallel simple cell mapping algorithm has two features: the number of cells in the invariant set grows linearly with the rolling subdivisions, and the Pareto set is insensitive to the inital set of seed cells. The current control design is compared with the classical LQE control for linear systems, and is also experimentally validated. The current design provides improved control performance as compares with the LQR control, and is applicable to complex nonlinear systems. },
keywords = {multi-objective optimization, parallel simple cell mapping, subdivision, tracking motion control, twin rotor helicopter},
language = {English},
publisher = {John Wiley & Sons, Ltd.}
}

This paper presents a study of multi‐objective optimal design of nonlinear control systems and has validated the control design with a twin rotor model helicopter. The gains of the porportional integral differential (PID) control are designed in the framework of multi‐objective opitmization. Eight design paramaters are optimized to minimize six time‐domain objective objective functions. The study of multi‐objective optimal design of feedback control with such a number of design paramaters and objective functions is rare in the literature. The Pareto optimal solutions are obtained by the proposed parallel simple cell mapping method consisting of a robust Pareto set recovery algorithm and a rolling subdivision technique. The proposed parallel simple cell mapping algorithm has two features: the number of cells in the invariant set grows linearly with the rolling subdivisions, and the Pareto set is insensitive to the inital set of seed cells. The current control design is compared with the classical LQE control for linear systems, and is also experimentally validated. The current design provides improved control performance as compares with the LQR control, and is applicable to complex nonlinear systems.

@article{xu_2019,
title = {Observer-Based Multi-Agent System Fault Upper Bound Estimation and Fault-Tolerant Consensus Control},
author = {Xu, M.; Yang, P.; Wang, Y.; Shu, Q.},
journal = {International Journal of Innovative Computing, Information and Control},
year = {2019},
volume = {15},
number = {2},
institution = {Nanjing University of Aeronautics and Astronautics, China},
abstract = {This paper investigates the consistency of multi-agent system with actuator fault. By constructing an appropriate observer, an adaptive algorithm for the upper bound of actuator fault factor is proposed. Subsequently, a fault-tolerant control law was proposed by using the relative state information between agents and the estimated value of the fault upper bound. Moreover, by the related theory of Lyapunov, we prove the theoretical feasibility of the algorithm in realizing the consistency of multi-agent system with actuator fault and external disturbance. Finally, a numerical simulation example verifies the effectiveness of the proposed algorithm and a comparative experiment demonstrates the superiority of the proposed algorithm. },
issn = {1349-4198},
keywords = {Multi-agent system, State observer, Fault-tolerant control, Adaptive control},
language = {English},
publisher = {ICIC International},
pages = {519-534}
}

This paper investigates the consistency of multi-agent system with actuator fault. By constructing an appropriate observer, an adaptive algorithm for the upper bound of actuator fault factor is proposed. Subsequently, a fault-tolerant control law was proposed by using the relative state information between agents and the estimated value of the fault upper bound. Moreover, by the related theory of Lyapunov, we prove the theoretical feasibility of the algorithm in realizing the consistency of multi-agent system with actuator fault and external disturbance. Finally, a numerical simulation example verifies the effectiveness of the proposed algorithm and a comparative experiment demonstrates the superiority of the proposed algorithm.

@article{xiloyannis_2019,
title = {Physiological and kinematic effects of a soft exosuit on arm movements},
author = {Xiloyannis, M.; Chiaradia, D.; Frisoli, A.; Masia, L.},
journal = {Journal of NeuroEngineering and Rehabilitation},
year = {2019},
volume = {16},
number = {29},
institution = {Nanyang Technological University, Singapore; Scuola Superiore Sant’Anna, Italy; Heidelberg University, Germany},
abstract = {Background: Soft wearable robots (exosuits), being lightweight, ergonomic and low power-demanding, are attractive for a variety of applications, ranging from strength augmentation in industrial scenarios, to medical assistance for people with motor impairments. Understanding how these devices affect the physiology and mechanics of human movements is fundamental for quantifying their benefits and drawbacks, assessing their suitability for different applications and guiding a continuous design refinement. Methods: We present a novel wearable exosuit for assistance/augmentation of the elbow and introduce a controller that compensates for gravitational forces acting on the limb while allowing the suit to cooperatively move with its wearer. Eight healthy subjects wore the exosuit and performed elbow movements in two conditions: with assistance from the device (powered) and without assistance (unpowered). The test included a dynamic task, to evaluate the impact of the assistance on the kinematics and dynamics of human movement, and an isometric task, to assess its influence on the onset of muscular fatigue. Results: Powered movements showed a low but significant degradation in accuracy and smoothness when compared to the unpowered ones. The degradation in kinematics was accompanied by an average reduction of 59.20±5.58% (mean ± standard error) of the biological torque and 64.8±7.66% drop in muscular effort when the exosuit assisted its wearer. Furthermore, an analysis of the electromyographic signals of the biceps brachii during the isometric task revealed that the exosuit delays the onset of muscular fatigue. Conclusions: The study examined the effects of an exosuit on the characteristics of human movements. The suit supports most of the power needed to move and reduces the effort that the subject needs to exert to counteract gravity in a static posture, delaying the onset of muscular fatigue. We interpret the decline in kinematic performance as a technical limitation of the current device. This work suggests that a powered exosuit can be a good candidate for industrial and clinical applications, where task efficiency and hardware transparency are paramount. },
issn = {1743-0003},
keywords = {soft exosuit, assistive wearable robot, human-robot interaction, kinematics, muscular fatigue, electromyography},
language = {English},
publisher = {Springer Nature}
}

Background: Soft wearable robots (exosuits), being lightweight, ergonomic and low power-demanding, are attractive for a variety of applications, ranging from strength augmentation in industrial scenarios, to medical assistance for people with motor impairments. Understanding how these devices affect the physiology and mechanics of human movements is fundamental for quantifying their benefits and drawbacks, assessing their suitability for different applications and guiding a continuous design refinement.
Methods: We present a novel wearable exosuit for assistance/augmentation of the elbow and introduce a controller that compensates for gravitational forces acting on the limb while allowing the suit to cooperatively move with its wearer. Eight healthy subjects wore the exosuit and performed elbow movements in two conditions: with assistance from the device (powered) and without assistance (unpowered). The test included a dynamic task, to evaluate the impact of the assistance on the kinematics and dynamics of human movement, and an isometric task, to assess its influence on the onset of muscular fatigue.
Results: Powered movements showed a low but significant degradation in accuracy and smoothness when compared to the unpowered ones. The degradation in kinematics was accompanied by an average reduction of 59.20±5.58% (mean ± standard error) of the biological torque and 64.8±7.66% drop in muscular effort when the exosuit assisted its wearer. Furthermore, an analysis of the electromyographic signals of the biceps brachii during the isometric task revealed that the exosuit delays the onset of muscular fatigue.
Conclusions: The study examined the effects of an exosuit on the characteristics of human movements. The suit supports most of the power needed to move and reduces the effort that the subject needs to exert to counteract gravity in a static posture, delaying the onset of muscular fatigue. We interpret the decline in kinematic performance as a technical limitation of the current device. This work suggests that a powered exosuit can be a good candidate for industrial and clinical applications, where task efficiency and hardware transparency are paramount.

@conference{wu2_2019,
title = {Preliminary Results Towards Reinforcement Learning with Mixed-signal Memristive Neuromorphic Circuits},
author = {Wu, N.; Vincent, A.F.; Strukov, D.},
booktitle = {IEEE International Symposium on Circuits and Systems (ISCAS) 2019},
year = {2019},
institution = {University of California Santa Barabra, USA},
abstract = {As the end of Moore's law seems to be imminent, emerging technologies that enable high performance neuromorphic hardware systems are attracting increasing attention. A very promising approach is to utilize memristors, programmable nonvolatile memory devices, as synaptic weights in neuromorphic circuits. One of the challenges for memristive hardware with integrated learning capabilities is prohibitively larger number of write cycles that might be required during learning process. In this work we propose a memristive neuromorphic hardware implementation for reinforcement learning based on temporal difference actor-critic algorithm. As a case study, we consider a task of balancing an inverted pendulum, a classical problem in both reinforcement learning and control theory. We introduce training techniques that significantly reduce the number of weight updates and are suitable for efficient in-situ learning hardware implementations. We believe that this study shows the promise of using memristor-based hardware neural networks for handling complex tasks through in-situ reinforcement learning. },
keywords = {Artificial neural networks; Reinforcement learning; Memristor; ReRAM; In-situ training; Hardware implementation; Actor-Critic model},
language = {English},
publisher = {IEEE}
}

As the end of Moore's law seems to be imminent, emerging technologies that enable high performance neuromorphic hardware systems are attracting increasing attention. A very promising approach is to utilize memristors, programmable nonvolatile memory devices, as synaptic weights in neuromorphic circuits. One of the challenges for memristive hardware with integrated learning capabilities is prohibitively larger number of write cycles that might be required during learning process. In this work we propose a memristive neuromorphic hardware implementation for reinforcement learning based on temporal difference actor-critic algorithm. As a case study, we consider a task of balancing an inverted pendulum, a classical problem in both reinforcement learning and control theory. We introduce training techniques that significantly reduce the number of weight updates and are suitable for efficient in-situ learning hardware implementations. We believe that this study shows the promise of using memristor-based hardware neural networks for handling complex tasks through in-situ reinforcement learning.

@article{chang_2019,
title = {Pseudo-Dynamic Test for Soil-Structure Interaction Analysis using Shake Tables},
author = {Chang, M.; Kim, .K.},
journal = {KSCE Journal of Civil Enineering},
year = {2019},
institution = {Korea Railroad Research Institute, Korea; Seoul National University, Korea},
abstract = {This paper presents an effective pseudo-dynamic (PSD) test method for analyzing the response of a multi degree of freedom structural system. In addition to the physical and numerical substructuring of the structure, the effect of the soil-structure interaction (SSI) is numerically modeled without a large soil box. The governing equation is separated into those for the superstructure and the base. These are coupled equations that can be solved recursively with the prediction of the superstructure acceleration, for which polynomial extrapolation is employed. The input for the structure is then obtained by solving the coupled equilibrium equations for experimental and analytically modeled systems. The restoring force applied underneath the superstructure is measured and used to update the superstructure acceleration. The stability condition for the proposed method is investigated, revealing a longer range of the convergence criterion than the Newmark explicit method. The implicit feature of the proposed method enables PSD tests irrespective of the modal properties, if the sampling frequency condition is satisfied. Additionally, the amplitude decay and period elongation are investigated for accuracy comparison in the structural responses. A series of PSD tests are performed using a two degree of freedom shear-building model to validate the proposed method. The experiment is performed on one part of the physical structure, while a numerical simulation is performed on the other part of the structure and on the SSI. The test results confirm that the proposed PSD algorithm is reliable for simulating the substructure and SSI effect. },
issn = {1226-7988},
keywords = {pseudo-dynamic test, shake table, soil-structure interaction, polynomial extrapolation, stability condition, substructure test},
language = {English},
publisher = {Korean Society of Civil Engineers}
}

This paper presents an effective pseudo-dynamic (PSD) test method for analyzing the response of a multi degree of freedom structural system. In addition to the physical and numerical substructuring of the structure, the effect of the soil-structure interaction (SSI) is numerically modeled without a large soil box. The governing equation is separated into those for the superstructure and the base. These are coupled equations that can be solved recursively with the prediction of the superstructure acceleration, for which polynomial extrapolation is employed. The input for the structure is then obtained by solving the coupled equilibrium equations for experimental and analytically modeled systems. The restoring force applied underneath the superstructure is measured and used to update the superstructure acceleration. The stability condition for the proposed method is investigated, revealing a longer range of the convergence criterion than the Newmark explicit method. The implicit feature of the proposed method enables PSD tests irrespective of the modal properties, if the sampling frequency condition is satisfied. Additionally, the amplitude decay and period elongation are investigated for accuracy comparison in the structural responses. A series of PSD tests are performed using a two degree of freedom shear-building model to validate the proposed method. The experiment is performed on one part of the physical structure, while a numerical simulation is performed on the other part of the structure and on the SSI. The test results confirm that the proposed PSD algorithm is reliable for simulating the substructure and SSI effect.

@inproceedings{ozdagli_2019,
title = {Real-Time Low-Cost Wireless Reference-Free Displacement Sensing of Railroad Bridges},
author = {Ozdagli A.; Liu B.; Moreu F. },
booktitle = {Sensors and Instrumentation, Aircraft/Aerospace and Energy Harvesting},
year = {2019},
volume = {8},
institution = {University of New Mexico, USA; Beijing Municipal Institute of Labour Protection, China},
abstract = {The U.S. freight rail network moves about 40 tons of freight per person over 225,000 km (140,000 miles) of rail track every year. The railroad infrastructure contains more than 100,000 bridges, which correspond to one bridge for every 2.25 km (1.4 miles) of track. Railroad resources and funds are limited. Consequently, railroads’ maintenance, repair, and replacement (MRR) decisions should be optimized. An objective prioritization of MRR decisions requires quantitative data that informs the structural integrity. Lateral displacement measurement of bridges is an objective and quantitative performance indicator. Traditional wired displacement measurement systems are costly, labor-intensive, and are difficult to apply on bridges due to the need of stationary reference points. This paper proposes an Arduino-based low-cost wireless sensing system to estimate bridge displacements from acceleration data. The system uses a low-cost MMA8451 accelerometer and implements a FIR-filter to convert the measurements to displacement. The data is transmitted to the base station using a XBee Series 1 module in real-time. Each sensor platform is estimated to cost about $75. To evaluate the feasibility of the proposed system, a set of laboratory experiments are conducted by placing the sensor platform on a shake table and simulating bridge displacements measured on the field during train crossing events. The proposed measurement system can have impact on many applications that need real-time displacement information including, but not limited to aerospace engineering, mechanical engineering, and wind engineering. },
keywords = {Wireless sensing, Low-cost sensing, Real-time sensing, Acceleration, Reference-free displacement estimation },
language = {English},
publisher = {Springer, Cham},
isbn = {978-3-319-74641-8}
}

The U.S. freight rail network moves about 40 tons of freight per person over 225,000 km (140,000 miles) of rail track every year. The railroad infrastructure contains more than 100,000 bridges, which correspond to one bridge for every 2.25 km (1.4 miles) of track. Railroad resources and funds are limited. Consequently, railroads’ maintenance, repair, and replacement (MRR) decisions should be optimized. An objective prioritization of MRR decisions requires quantitative data that informs the structural integrity. Lateral displacement measurement of bridges is an objective and quantitative performance indicator. Traditional wired displacement measurement systems are costly, labor-intensive, and are difficult to apply on bridges due to the need of stationary reference points. This paper proposes an Arduino-based low-cost wireless sensing system to estimate bridge displacements from acceleration data. The system uses a low-cost MMA8451 accelerometer and implements a FIR-filter to convert the measurements to displacement. The data is transmitted to the base station using a XBee Series 1 module in real-time. Each sensor platform is estimated to cost about $75. To evaluate the feasibility of the proposed system, a set of laboratory experiments are conducted by placing the sensor platform on a shake table and simulating bridge displacements measured on the field during train crossing events. The proposed measurement system can have impact on many applications that need real-time displacement information including, but not limited to aerospace engineering, mechanical engineering, and wind engineering.

@article{kyeong_2019,
title = {Recognition of walking environments and gait period by surface electromyography},
author = {Kyeong, S.; Shin, W.; Yang, M.; Heo, U.; Feng, J.-r.; Kim, J.},
journal = {Frontiers of Information Technology & Electronic Engineering},
year = {2019},
month = {03},
volume = {20},
number = {3},
institution = {Korea Advanced Institute of Science and Technology (KAIST), Korea},
abstract = {Recognizing and predicting the movement and intention of the wearer in control of an exoskeleton robot is very challenging. It is difficult for exoskeleton robots, which measure and drive human movements, to interact with humans. Therefore, many different types of sensors are needed. When using various sensors, a data design is needed for effective sensing. An electromyographic (EMG) signal can be used to identify intended motion before the actual movement, and the delay time can be shortened via control of the exoskeleton robot. Before using a lower limb exoskeleton to help in walking, the aim of this work is to distinguish the walking environment and gait period using various sensors, including the surface electromyography (sEMG) sensor. For this purpose, a gait experiment was performed on four subjects using the ground reaction force, human-robot interaction force, and position sensors with sEMG sensors. The purpose of this paper is to show progress with the use of sEMG when recognizing walking environments and the gait period with other sensors. For effective data design, we used a combination of sensor types, sEMG sensor locations, and sEMG features. The results obtained using an individual mechanical sensor together with sEMG showed improvement compared to the case of using an individual sensor, and the combination of sEMG and position information showed the best performance in the same number of combinations of three sensors. When four sensor combinations were used, the environment classification accuracy was 96.1%, and the gait period classification accuracy was 97.8%. Vastus medialis (VM) and gastrocnemius (GAS) were the most effective combinations of two muscle types among the five sEMG sensor locations on the legs, and the results were 74.4% in pre-heel contact (preHC) and 71.7% in pre-toe-off (preTO) for environment classification, and 68.0% for gait period classification, when using only the sEMG sensor. The two effective sEMG feature combinations were “mean absolute value (MAV), zero crossings (ZC)” and “MAV, waveform length (WL)”, and the “MAV, ZC” results were 80.0%, 77.1%, and 75.5%. These results suggest that the sEMG signal can be effectively used to control an exoskeleton robot. },
issn = {2095-9184},
keywords = {Walking environment, Gait Period, Surface electromyography (sEMG), Exoskeleton },
language = {English},
publisher = {Springer Nature}
}

Recognizing and predicting the movement and intention of the wearer in control of an exoskeleton robot is very challenging. It is difficult for exoskeleton robots, which measure and drive human movements, to interact with humans. Therefore, many different types of sensors are needed. When using various sensors, a data design is needed for effective sensing. An electromyographic (EMG) signal can be used to identify intended motion before the actual movement, and the delay time can be shortened via control of the exoskeleton robot. Before using a lower limb exoskeleton to help in walking, the aim of this work is to distinguish the walking environment and gait period using various sensors, including the surface electromyography (sEMG) sensor. For this purpose, a gait experiment was performed on four subjects using the ground reaction force, human-robot interaction force, and position sensors with sEMG sensors. The purpose of this paper is to show progress with the use of sEMG when recognizing walking environments and the gait period with other sensors. For effective data design, we used a combination of sensor types, sEMG sensor locations, and sEMG features. The results obtained using an individual mechanical sensor together with sEMG showed improvement compared to the case of using an individual sensor, and the combination of sEMG and position information showed the best performance in the same number of combinations of three sensors. When four sensor combinations were used, the environment classification accuracy was 96.1%, and the gait period classification accuracy was 97.8%. Vastus medialis (VM) and gastrocnemius (GAS) were the most effective combinations of two muscle types among the five sEMG sensor locations on the legs, and the results were 74.4% in pre-heel contact (preHC) and 71.7% in pre-toe-off (preTO) for environment classification, and 68.0% for gait period classification, when using only the sEMG sensor. The two effective sEMG feature combinations were “mean absolute value (MAV), zero crossings (ZC)” and “MAV, waveform length (WL)”, and the “MAV, ZC” results were 80.0%, 77.1%, and 75.5%. These results suggest that the sEMG signal can be effectively used to control an exoskeleton robot.

@article{trimpe_2019,
title = {Resource-aware IoT Control: Saving Communication through Predictive Triggering},
author = {Trimpe, S.; Baumann, D.},
year = {2019},
institution = { Max Planck Institute for Intelligent Systems, Germany},
abstract = {The Internet of Things (IoT) interconnects multiple physical devices in large-scale networks. When the ‘things’ coordinate decisions and act collectively on shared information, feedback is introduced between them. Multiple feedback loops are thus closed over a shared, general-purpose network. Traditional feedback control is unsuitable for design of IoT control because it relies on high-rate periodic communication and is ignorant of the shared network resource. Therefore, recent event-based estimation methods are applied herein for resource-aware IoT control allowing agents to decide online whether communication with other agents is needed, or not. While this can reduce network traffic significantly, a severe limitation of typical event-based approaches is the need for instantaneous triggering decisions that leave no time to reallocate freed resources (e.g., communications lots), which hence remain unused. To address this problem, novel predictive and self triggering protocols are proposed herein. From a unified Bayesian decision framework, two schemes are developed: self triggers that predict, at the current triggering instant, the next one; and predictive triggers that check at everytime step, whether communication will be needed at a given prediction horizon. The suitability of these triggers for feedback control is demonstrated in hardware experiments on a cart-pole, and scalability is discussed with a multi-vehicle simulation. },
keywords = {Internet of Things, feedback control, event-based state estimation, predictive triggering, self triggering, distributed control, resource-aware control},
language = {English}
}

The Internet of Things (IoT) interconnects multiple physical devices in large-scale networks. When the ‘things’ coordinate decisions and act collectively on shared information, feedback is introduced between them. Multiple feedback loops are thus closed over a shared, general-purpose network. Traditional feedback control is unsuitable for design of IoT control because it relies on high-rate periodic communication and is ignorant of the shared network resource. Therefore, recent event-based estimation methods are applied herein for resource-aware IoT control allowing agents to decide online whether communication with other agents is needed, or not. While this can reduce network traffic significantly, a severe limitation of typical event-based approaches is the need for instantaneous triggering decisions that leave no time to reallocate freed resources (e.g., communications lots), which hence remain unused. To address this problem, novel predictive and self triggering protocols are proposed herein. From a unified Bayesian decision framework, two schemes are developed: self triggers that predict, at the current triggering instant, the next one; and predictive triggers that check at everytime step, whether communication will be needed at a given prediction horizon. The suitability of these triggers for feedback control is demonstrated in hardware experiments on a cart-pole, and scalability is discussed with a multi-vehicle simulation.

@article{chhabra_2019,
title = {Robust nonlinear fractional order fuzzy PD plus fuzzy I controller applied to robotic manipulator},
author = {Chhabra, H.; Mohan, V.; Rani, A.; Singh, V.},
journal = {Neural Computing and Applications},
year = {2019},
institution = {Netaji Subhas Institute of Technology, India},
abstract = {The aim of this article is to utilize fractional calculus for performance enhancement of nonlinear fuzzy PD + I controller. A fractional order fuzzy PD + I controller (FOFPD + I) is designed and implemented to control complex, uncertain and nonlinear robotic manipulator. FOFPD + I controller is derived from fractional order PD and fractional order I controller. The proposed control strategy has an adaptive capability due to its nonlinear gains and preserves the linear structure of fractional order PD + I controller. Further, integer-order fuzzy PD + I controller (FPD + I) and conventional PID controllers are also designed for comparative analysis. The optimum parameter values of FOFPD + I, FPD + I and PID controllers are obtained using non-dominated sorting genetic algorithm-II. The effectiveness of proposed controller is examined for reference tracking and disturbance rejection problems of robotic manipulator. The designed controllers are also validated experimentally on DC servomotor. Simulation and experimental results prove the superiority of FOFPD + I controller as compared to its integer-order equivalent and conventional PID controllers for control of robotic manipulator. },
issn = {0941-0643},
keywords = {FOFPD + I, FPD + I, NSGA-II, Robotic manipulator },
language = {English},
publisher = {Springer London}
}

The aim of this article is to utilize fractional calculus for performance enhancement of nonlinear fuzzy PD + I controller. A fractional order fuzzy PD + I controller (FOFPD + I) is designed and implemented to control complex, uncertain and nonlinear robotic manipulator. FOFPD + I controller is derived from fractional order PD and fractional order I controller. The proposed control strategy has an adaptive capability due to its nonlinear gains and preserves the linear structure of fractional order PD + I controller. Further, integer-order fuzzy PD + I controller (FPD + I) and conventional PID controllers are also designed for comparative analysis. The optimum parameter values of FOFPD + I, FPD + I and PID controllers are obtained using non-dominated sorting genetic algorithm-II. The effectiveness of proposed controller is examined for reference tracking and disturbance rejection problems of robotic manipulator. The designed controllers are also validated experimentally on DC servomotor. Simulation and experimental results prove the superiority of FOFPD + I controller as compared to its integer-order equivalent and conventional PID controllers for control of robotic manipulator.

@article{assa_2019,
title = {Sample-based adaptive Kalman filtering for accurate camera pose tracking},
author = {Assa, A.; Janabi-Sharifi, F.; Plataniotisa, K.N.},
journal = {Neurocomputing},
year = {2019},
month = {03},
volume = {333},
institution = {University of Toronto, Canada; Ryerson University, Canada},
abstract = {Inferring the camera pose with high accuracy is deemed crucial in many applications such as robot manipulation and virtual reality. Traditionally, features extracted from camera images are processed by Kalman-based schemes due to their high efficacy and fast response. Yet, the performance of the filter deteriorates if the parameters of the filter are uncertain. Estimating the noise parameters through conventional adaptive schemes alleviates this problem, yet the estimation’s accuracy still suffers from rough parameter estimations. To improve the accuracy of pose estimations further, this work proposes a novel adaptive scheme which employs a multi-model approach to approximate the system posteriori via sampling the noise and initial state covariance priories and progressively adjusting the filter parameters using the drawn samples. The experimental results confirm the enhanced performance of the proposed adaptive method compared to previously applied adaptive and non-adaptive pose estimation schemes, at the expense of additional complexity. },
keywords = {Adaptive Kalman filtering, Vision-based pose estimation, Covariance sampling},
language = {English},
publisher = {Elsevier B.V.},
pages = {307-318}
}

Inferring the camera pose with high accuracy is deemed crucial in many applications such as robot manipulation and virtual reality. Traditionally, features extracted from camera images are processed by Kalman-based schemes due to their high efficacy and fast response. Yet, the performance of the filter deteriorates if the parameters of the filter are uncertain. Estimating the noise parameters through conventional adaptive schemes alleviates this problem, yet the estimation’s accuracy still suffers from rough parameter estimations. To improve the accuracy of pose estimations further, this work proposes a novel adaptive scheme which employs a multi-model approach to approximate the system posteriori via sampling the noise and initial state covariance priories and progressively adjusting the filter parameters using the drawn samples. The experimental results confirm the enhanced performance of the proposed adaptive method compared to previously applied adaptive and non-adaptive pose estimation schemes, at the expense of additional complexity.