@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{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{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{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{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{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.

@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{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{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.

@article{geng_2019,
title = {Six‐Degree‐of‐Freedom Broadband Seismogeodesy by Combining Collocated High‐Rate GNSS, Accelerometers, and Gyroscopes},
author = {Geng, J.; Wen, Q.; Chen, Q.; Chang, H.},
journal = {Geophysical Research Letters},
year = {2019},
institution = {Wuhan University, China},
abstract = {Combining collocated high‐rate Global Navigation Satellite Systems (GNSS) and accelerometers produces broadband seismogeodetic displacements. However, accelerometer data must be heavily downweighted due to their baseline errors originating primarily in instrument rotations, and therefore their contribution to seismogeodetic displacements is seriously underestimated. We further introduced a gyroscope into this classic seismogeodesy to mitigate baseline errors and formulated advanced six‐degree‐of‐freedom (6‐DOF) seismogeodesy without undervaluing accelerometer data. A shake table holding one GNSS antenna, four accelerometers, and one gyroscope was used to simulate waveforms from the 2010 Mw 7.2 El Mayor‐Cucapah earthquake. We found that the displacements derived from the 6‐DOF seismogeodesy were up to 68% more accurate than those from the classic seismogeodesy over 0.04–0.4 Hz. Moreover, broadband rotations containing the permanent components were also generated, which were unachievable by integrating gyroscope data. We believe that the 6‐DOF seismogeodesy is capable of improving both source rupture studies of large earthquakes and high‐rise monitoring under strong seismic waves. },
language = {English},
publisher = {John Wiley & Sons, Ltd.}
}

Combining collocated high‐rate Global Navigation Satellite Systems (GNSS) and accelerometers produces broadband seismogeodetic displacements. However, accelerometer data must be heavily downweighted due to their baseline errors originating primarily in instrument rotations, and therefore their contribution to seismogeodetic displacements is seriously underestimated. We further introduced a gyroscope into this classic seismogeodesy to mitigate baseline errors and formulated advanced six‐degree‐of‐freedom (6‐DOF) seismogeodesy without undervaluing accelerometer data. A shake table holding one GNSS antenna, four accelerometers, and one gyroscope was used to simulate waveforms from the 2010 Mw 7.2 El Mayor‐Cucapah earthquake. We found that the displacements derived from the 6‐DOF seismogeodesy were up to 68% more accurate than those from the classic seismogeodesy over 0.04–0.4 Hz. Moreover, broadband rotations containing the permanent components were also generated, which were unachievable by integrating gyroscope data. We believe that the 6‐DOF seismogeodesy is capable of improving both source rupture studies of large earthquakes and high‐rise monitoring under strong seismic waves.

@article{mehedi_2019,
title = {Two degrees of freedom fractional controller design: Application to the ball and beam system},
author = {Mehedi, I.M.; Al-Saggaf, U.M.; Mansouri, R.; Bettayeb, M.},
journal = {Measurement},
year = {2019},
month = {03},
volume = {135},
institution = { King Abdulaziz University, Saudi Arabia; Mouloud Mammeri University, Algeria; University of Sharjah, United Arab Emirates},
abstract = {Control engineers and researchers face challenges to design an efficient controller for Ball and beam system due to its nonlinear and unstable properties. This paper investigates two Degrees of Freedom fractional order control of the ball and beam system. It involves the model based method to design controllers’ parameters for the corresponding linear model. The fractional order controllers are specially tuned to have a constant phase margin of the open-loop. This characteristic ensures the robustness of the controllers to the variations of system gain. This paper presents a proper evaluation and comparison between integer and fractional order controllers. Performance of each controller is evaluated in terms of set-point tracking, disturbance rejection, and robustness. The comparison between two controllers is validated through both simulation and experimental results. Strengths and weaknesses in the real-time control are also indicated. },
keywords = {Fractional order controller, PD controllers, Internal model control, Unstable system, Robust control, Ball and beam system},
language = {English},
publisher = {Elsevier Ltd.},
pages = {13-22}
}

Control engineers and researchers face challenges to design an efficient controller for Ball and beam system due to its nonlinear and unstable properties. This paper investigates two Degrees of Freedom fractional order control of the ball and beam system. It involves the model based method to design controllers’ parameters for the corresponding linear model. The fractional order controllers are specially tuned to have a constant phase margin of the open-loop. This characteristic ensures the robustness of the controllers to the variations of system gain. This paper presents a proper evaluation and comparison between integer and fractional order controllers. Performance of each controller is evaluated in terms of set-point tracking, disturbance rejection, and robustness. The comparison between two controllers is validated through both simulation and experimental results. Strengths and weaknesses in the real-time control are also indicated.

@article{furtado2_2018,
title = {3-D UAV Path Planning in a Cluttered Environment using PSO},
author = {Furtado, J.S.; Liu, H.H.T.},
year = {2018},
institution = {University of Toronto Institute for Aerospace Studies, Canada},
abstract = {The use of Unmanned Aerial Vehicles (UAVs) in a wide variety of civilian and military applications such as surveillance, inspection, and precision agriculture has become increasingly popular over the last few years. The performance of the mission is based on the time taken to complete the mission. Path planning is therefore a key component in most UAV applications. The main objective of this work is to plan efficient three-dimensional (3-D) paths for a UAV to get from its start location to its goal location avoiding any collision with obstacles in the environment. Based on literature review, Swarm Intelligence (SI) based algorithm, Particle Swarm Optimisation (PSO) is utilised to generate collision free trajectories for a UAV in a cluttered environment. SI is an innovative distributed and intelligent paradigm used for solving optimization problems. It is inherently robust, scalable and stochastic, inspired by the collective behaviour seen in biological systems. The objective function being optimised is the length of the path to be own by the UAV subject to collision constraints. The algorithm generates discrete waypoints using which a smooth flyable path is generated by spline interpolation. Simulation as well as experimental results are shown to demonstrate the results of this work after testing in different scenarios. },
language = {English}
}

The use of Unmanned Aerial Vehicles (UAVs) in a wide variety of civilian and military applications such as surveillance, inspection, and precision agriculture has become increasingly popular over the last few years. The performance of the mission is based on the time taken to complete the mission. Path planning is therefore a key component in most UAV applications. The main objective of this work is to plan efficient three-dimensional (3-D) paths for a UAV to get from its start location to its goal location avoiding any collision with obstacles in the environment. Based on literature review, Swarm Intelligence (SI) based algorithm, Particle Swarm Optimisation (PSO) is utilised to generate collision free trajectories for a UAV in a cluttered environment. SI is an innovative distributed and intelligent paradigm used for solving optimization problems. It is inherently robust, scalable and stochastic, inspired by the collective behaviour seen in biological systems. The objective function being optimised is the length of the path to be own by the UAV subject to collision constraints. The algorithm generates discrete waypoints using which a smooth flyable path is generated by spline interpolation. Simulation as well as experimental results are shown to demonstrate the results of this work after testing in different scenarios.

@inproceedings{erwin_2018,
title = {A Bowden Cable-Based Series Elastic Actuation Module for Assessing the Human Wrist},
author = {Erwin, A.; Moser, N.; McDonald, C.G.; O’Malley, M.K. },
booktitle = {ASME 2018 Dynamic Systems and Control Conference (DSCC2018)},
year = {2018},
institution = {Rice University, TX, USA},
abstract = {Currently, wrist passive stiffness and active range of motion, two clinically relevant properties, are assessed using devices designed for rehabilitation. As a result, these devices do not have sufficient torque output and range of motion for complete wrist biomechanical assessment. To address these limitations, we are developing an actuation module specifically for assessing wrist biomechanical properties. Our device employs a serial kinematic exoskeletal architecture to directly interact with and measure wrist flexion/extension and radial/ulnar deviation. A Bowden cable-based actuation scheme, locating the motors off-board, was adopted for increased device range of motion and torque output compared with previous wrist exoskeletons. Additionally, the device was designed to incorporate a rotational elastic element at each joint, creating series elastic actuators, for accurate torque control and direct torque measurement. In this work, we present the design and demonstration of a 1-DOF module of the device, which can interact with a user’s wrist in flexion/extension, providing an important first step towards the control, evaluation, and application of the 2-DOF device. },
language = {English},
publisher = {ASME},
isbn = { 978-0-7918-5189-0}
}

Currently, wrist passive stiffness and active range of motion, two clinically relevant properties, are assessed using devices designed for rehabilitation. As a result, these devices do not have sufficient torque output and range of motion for complete wrist biomechanical assessment. To address these limitations, we are developing an actuation module specifically for assessing wrist biomechanical properties. Our device employs a serial kinematic exoskeletal architecture to directly interact with and measure wrist flexion/extension and radial/ulnar deviation. A Bowden cable-based actuation scheme, locating the motors off-board, was adopted for increased device range of motion and torque output compared with previous wrist exoskeletons. Additionally, the device was designed to incorporate a rotational elastic element at each joint, creating series elastic actuators, for accurate torque control and direct torque measurement. In this work, we present the design and demonstration of a 1-DOF module of the device, which can interact with a user’s wrist in flexion/extension, providing an important first step towards the control, evaluation, and application of the 2-DOF device.

@article{kammer_2018,
title = {A Data-Driven Fixed-Structure Control Design Method with Application to a 2-DOF Gyroscope},
author = {Kammer, C.; Karimi, A.},
year = {2018},
institution = {Laboratoire d’Automatique, Ecole Polytechnique Federale de Lausanne, Switzerland},
abstract = {This paper presents the practical aspects and application of a novel data-driven, fixed-structure, robust control design method. Only the frequency response data of the system is needed for the design, and no parametric model is required. The method can be used to design fully parametrized continuous- or discrete-time matrix transfer function controllers. The control performance is specified as constraints on the H-infinity or H2 norm of weighted sensitivity functions, and a convex formulation of the robust design problem is proposed. An application of the presented method is explored on an experimental setup, where a multivariable controller for a gyroscope is designed based only on the measured frequency response of the system. },
language = {English}
}

This paper presents the practical aspects and application of a novel data-driven, fixed-structure, robust control design method. Only the frequency response data of the system is needed for the design, and no parametric model is required. The method can be used to design fully parametrized continuous- or discrete-time matrix transfer function controllers. The control performance is specified as constraints on the H-infinity or H2 norm of weighted sensitivity functions, and a convex formulation of the robust design problem is proposed. An application of the presented method is explored on an experimental setup, where a multivariable controller for a gyroscope is designed based only on the measured frequency response of the system.

@article{diaz_2018,
title = {A Filtered Sun Sensor for Solar Tracking in HCPV and CSP Systems},
author = {Diaz, A.; Garrido, R.; Soto-Bernal, JJ},
journal = {IEEE Sensors Journal},
year = {2018},
institution = {Centro de Investigaciones en Óptica, A.C., Mexico; CINVESTAV-IPN, Mexico; Instituto Tecnológico de Aguascalientes, Mexico},
abstract = {Tracking systems with stringent performance are required to take advantage of solar energy produced through the use of High Concentration Photovolatics (HCPV) and Concentrating Solar Power (CSP) technologies. Closed-loop tracking systems use measurements provided by a sun sensor, which picks up direct and diffuse sunlight. High levels of diffuse sunlight produce increased levels of measurement noise at the output of the sensor, which in turn limits the maximal achievable gains in the closed-loop controller and consequently the tracking performance deteriorates. The goal of this work is to present the advantages of equipping a four-quadrant photodiode sun sensor with infrared and linear polarizing optical filters. Experimental results show that these filters reduce the effect of diffuse radiation and allow increasing the performance of sun tracking systems regardless of the type of controller used in the solar tracker. Tracking experiments are presented under indoor and outdoor conditions employing algorithms currently used in solar trackers including Proportional-Integral (PI), and Proportional-Integral-Derivative (PID) controllers, and a recently proposed cascade control law. In all the cases, the best performance is obtained with the sun sensor equipped with an infrared filter. Experiments show that an infrared optical filter reduces the Filtered Mean Squared Tracking Error up to 75under artificial light conditions and 90% under direct sunlight. },
issn = {1558-1748},
keywords = {Sun sensor, photodiodes, solar tracker, HCPV, CSP, photovoltaic system, infrared filter, linear polarization filter, closed-loop control},
language = {English},
publisher = {IEEE}
}

Tracking systems with stringent performance are required to take advantage of solar energy produced through the use of High Concentration Photovolatics (HCPV) and Concentrating Solar Power (CSP) technologies. Closed-loop tracking systems use measurements provided by a sun sensor, which picks up direct and diffuse sunlight. High levels of diffuse sunlight produce increased levels of measurement noise at the output of the sensor, which in turn limits the maximal achievable gains in the closed-loop controller and consequently the tracking performance deteriorates. The goal of this work is to present the advantages of equipping a four-quadrant photodiode sun sensor with infrared and linear polarizing optical filters. Experimental results show that these filters reduce the effect of diffuse radiation and allow increasing the performance of sun tracking systems regardless of the type of controller used in the solar tracker. Tracking experiments are presented under indoor and outdoor conditions employing algorithms currently used in solar trackers including Proportional-Integral (PI), and Proportional-Integral-Derivative (PID) controllers, and a recently proposed cascade control law. In all the cases, the best performance is obtained with the sun sensor equipped with an infrared filter. Experiments show that an infrared optical filter reduces the Filtered Mean Squared Tracking Error up to 75under artificial light conditions and 90% under direct sunlight.

@conference{abdullah_2018,
title = {A Formal Sensitivity Analysis for Laguerre Based Predictive Functional Control},
author = {Abdullah, M.; Rossiter, J.A.},
booktitle = {Control 2018 - 12th UKACC International Conference on Control},
year = {2018},
institution = {University of Sheffield, UK},
abstract = {A Laguerre Predictive Functional Control (LPFC) is a simple input shaping method, which can improve the prediction consistency and closed-loop performance of the conventional approach (PFC). However, it is well-known that an input shaping method, in general, will affect the loop sensitivity of a system. Hence, this paper presents a formal sensitivity analysis of LPFC by considering the effect of noise, unmeasured disturbance and parameter uncertainty. Sensitivity plots from bode diagrams and closed-loop simulation are used to illustrate the controller robustness and indicate that although LPFC often provides a better closed-loop tracking response and disturbance rejection, this may involve some trade-off with the sensitivity to noise and parameter uncertainty. Finally, to validate the practicality of the results, the sensitivity of the LPFC control law is illustrated on real-time laboratory hardware. },
keywords = {Predictive Control, PFC, Sensitivity Analysis, Laguerre function, Parameter Uncertainty, Noise, Disturbance},
language = {English},
publisher = {IEEE}
}

A Laguerre Predictive Functional Control (LPFC) is a simple input shaping method, which can improve the prediction consistency and closed-loop performance of the conventional approach (PFC). However, it is well-known that an input shaping method, in general, will affect the loop sensitivity of a system. Hence, this paper presents a formal sensitivity analysis of LPFC by considering the effect of noise, unmeasured disturbance and parameter uncertainty. Sensitivity plots from bode diagrams and closed-loop simulation are used to illustrate the controller robustness and indicate that although LPFC often provides a better closed-loop tracking response and disturbance rejection, this may involve some trade-off with the sensitivity to noise and parameter uncertainty. Finally, to validate the practicality of the results, the sensitivity of the LPFC control law is illustrated on real-time laboratory hardware.

@article{zhao_2018,
title = {A Frequency Adaptive PIMR-Type Repetitive Control for a Grid-Tied Inverter},
author = {Zhao, Q.; Chen, S.; Wen, S.},
year = {2018},
institution = {Zhongyuan University of Technology, China},
abstract = { A proportional integral multiresonant-type repetitive control (PIMR-type RC) has not only a better harmonic suppressing performance but also a faster error convergence rate. However, the harmonics suppressing performance of PIMRtype RC will significantly decrease when the grid fundamental frequency fluctuates in a large range. In this paper, an improved frequency adaptive PIMR-type RC (FA-PIMR-type RC) is proposed to cope with the frequency fluctuation in a large range. The improved PIMR-type RC is based on fractional delay filter which can be approximately realized by finite impulse response (FIR) filter. The varying fractional delay filters ensure that the resonant frequencies can match the actual reference frequency and harmonic frequencies. The synthesis, stability analysis, and parameters design criteria of the proposed FA-PIMR-type RC are given in this paper. The simulation and experimental results show that the improved PIMR-type RC can track grid reference signal, suppress harmonic signals and have good error convergence rate under grid frequency fluctuation. },
issn = {2169-3536 },
keywords = {Grid-tied inverter, repetitive control (RC), FIR filter, frequency adaptive PIMR-type RC},
language = {English},
publisher = {IEEE}
}

A proportional integral multiresonant-type repetitive control (PIMR-type RC) has not only a better harmonic suppressing performance but also a faster error convergence rate. However, the harmonics suppressing performance of PIMRtype RC will significantly decrease when the grid fundamental frequency fluctuates in a large range. In this paper, an improved frequency adaptive PIMR-type RC (FA-PIMR-type RC) is proposed to cope with the frequency fluctuation in a large range. The improved PIMR-type RC is based on fractional delay filter which can be approximately realized by finite impulse response (FIR) filter. The varying fractional delay filters ensure that the resonant frequencies can match the actual reference frequency and harmonic frequencies. The synthesis, stability analysis, and parameters design criteria of the proposed FA-PIMR-type RC are given in this paper. The simulation and experimental results show that the improved PIMR-type RC can track grid reference signal, suppress harmonic signals and have good error convergence rate under grid frequency fluctuation.

@article{lucia_2018,
title = {A Hybrid Command Governor Scheme for Rotary Wings Unmanned Aerial Vehicles},
author = {Lucia, W.; Franze, G.; Sznaier, M.},
journal = {IEEE Transactions on Control Systems Technology},
year = {2018},
institution = {Concordia University, Canada; University of Calabria, Italy; Northeastern University, USA},
abstract = {In this paper, we develop an obstacle avoidance control scheme for autonomous aerial vehicles. The strategy is based on command governor (CG) ideas that are here extended to take into account nonconvex constraints typically arising in path planning obstacle avoidance problems. As one of its main merits, the collision avoidance task is accomplished by exploiting convex inner approximations of the obstacle-free region and an ad hoc constraints switching procedure which significantly reduces the online computations pertaining to the CG design. Experimental results on the quadrotor Qball-X4 show the applicability and effectiveness of the proposed approach. },
keywords = {Constrained control, command governor, model predictive control, obstacle avoidance, rotary wings UAV, quadro- tor QBall-X4, unmanned aerial vehicles},
language = {English},
publisher = {IEEE}
}

In this paper, we develop an obstacle avoidance control scheme for autonomous aerial vehicles. The strategy is based on command governor (CG) ideas that are here extended to take into account nonconvex constraints typically arising in path planning obstacle avoidance problems. As one of its main merits, the collision avoidance task is accomplished by exploiting convex inner approximations of the obstacle-free region and an ad hoc constraints switching procedure which significantly reduces the online computations pertaining to the CG design. Experimental results on the quadrotor Qball-X4 show the applicability and effectiveness of the proposed approach.

@article{rose_2018,
title = {A Hybrid Rigid-Soft Hand Exoskeleton to Assist Functional Dexterity},
author = {Rose, C.; O'Malley, M.},
journal = {IEEE Robotics and Automation Letters},
year = {2018},
institution = {Rice University, TX, USA},
abstract = { A hybrid hand exoskeleton, leveraging rigid and soft elements, has been designed to serve as an assistive device to return the ability to perform activities of daily living (ADLs) and improve quality of life (QOL) for a broad population with hand impairment. This glove-like exoskeleton, the SeptaPose Assistive and Rehabilitative (SPAR) Glove, is underactuated, enabling seven hand poses which support most ADLs. The device resides on the spectrum between traditional rigid devices and the latest soft robotic designs. It includes novel ergonomic elements for power transmission and additional features to enable self-donning and doffing. Embedded sensors enable pose estimation and intent detection for intuitive control of the glove. In this paper, we summarize the overall design of the glove, and present details of the novel rigid palm bar and hyperextension prevention elements. We characterize the grasp force and range of motion (ROM) of the glove, and present initial feedback from an end-user. The SPAR Glove meets or exceeds the functional requirements of ADLs for both ROM and grasp force. Additionally, the glove exceeds the grasp force capabilities of comparable devices, while simultaneously offering the highest number of poses. In addition to its role as an assistive device, the SPAR Glove exoskeleton has the potential to provide "hands-in" rehabilitation centered on performing functional tasks. In the near term, the glove is a highly capable prototype for exploring hybrid assistive device design, intent detection, and user interface research. },
issn = {2377-3766 },
keywords = {Physically Assistive Devices, Wearable Robots, Rehabilitation Robotics, Prosthetics and Exoskeletons},
language = {English}
}

A hybrid hand exoskeleton, leveraging rigid and soft elements, has been designed to serve as an assistive device to return the ability to perform activities of daily living (ADLs) and improve quality of life (QOL) for a broad population with hand impairment. This glove-like exoskeleton, the SeptaPose Assistive and Rehabilitative (SPAR) Glove, is underactuated, enabling seven hand poses which support most ADLs. The device resides on the spectrum between traditional rigid devices and the latest soft robotic designs. It includes novel ergonomic elements for power transmission and additional features to enable self-donning and doffing. Embedded sensors enable pose estimation and intent detection for intuitive control of the glove. In this paper, we summarize the overall design of the glove, and present details of the novel rigid palm bar and hyperextension prevention elements. We characterize the grasp force and range of motion (ROM) of the glove, and present initial feedback from an end-user. The SPAR Glove meets or exceeds the functional requirements of ADLs for both ROM and grasp force. Additionally, the glove exceeds the grasp force capabilities of comparable devices, while simultaneously offering the highest number of poses. In addition to its role as an assistive device, the SPAR Glove exoskeleton has the potential to provide "hands-in" rehabilitation centered on performing functional tasks. In the near term, the glove is a highly capable prototype for exploring hybrid assistive device design, intent detection, and user interface research.

This article presents a model-based velocity controller able to induce a chaotic motion on n-degrees of freedom flexible joint robot manipulators. The proposed controller allows the velocity link vector of a robot manipulator to track an arbitrary, chaotic reference vector field. A rigorous theoretical analysis based on Lyapunov’s theory is used to prove the asymptotic stability of the tracking error signals when using the proposed controller, which implies that a chaotic motion is induced to the robotic system. Experimental results are provided using a flexible joint robot manipulator of two degrees of freedom. Finally, by using Poincaré maps and Lyapunov exponents, it is shown that the behavior exhibited by the robot joint positions is chaotic.

@article{ghannadi_2018,
title = {A modified homotopy optimization for parameter identification in dynamic systems with backlash discontinuity},
author = { Ghannadi, B.; Razavian, R.S.; McPhee, J.},
journal = {Nonlinear Dynamics},
year = {2018},
institution = {University of Waterloo, Canada},
abstract = {Model-based control considers system dynamics to solve challenging control problems; recently, the amount of activity in developing model-based controllers is growing, specifically in rehabilitation robotics. The performance of this controller depends on how accurate the system dynamics has been modeled. Dynamic parameter identification (DPI) of the systems is required for optimal performance of the model-based controller. Current DPI methods are more suitable for systems with continuous dynamics. If any type of discontinuity (e.g., backlash) is present in the system, the DPI may have numerical problems for convergence. In this work, we propose a modified homotopy optimization to identify parameters of a system with mechanical discontinuity (i.e., backlash). The performance of the proposed method was first evaluated through a computer simulation on a system with sandwiched backlash. Results of the DPI showed that the proposed homotopy optimization can identify the discontinuous system parameters with a good accuracy. It was found that ignoring the backlash in the system dynamics imposes large errors in the system DPI. After verifying the proposed method using computer simulations, the DPI was implemented to identify the parameters of a rehabilitation robot with actuator backlash. The proposed method provided a better estimate of the system parameters compared to the no-backlash DPI of the experimental robot. Despite the noise in velocity and acceleration due to the numerical differentiation of the sampled angle measurements, the forward dynamics results are quite accurate for all of the tested configurations with the discontinuous backlash model. },
issn = {0924-090X},
keywords = {Parameter identification, System dynamics, Sandwiched backlash, Homotopy optimization, Rehabilitation robot },
language = {English},
publisher = {Springer Netherlands}
}

Model-based control considers system dynamics to solve challenging control problems; recently, the amount of activity in developing model-based controllers is growing, specifically in rehabilitation robotics. The performance of this controller depends on how accurate the system dynamics has been modeled. Dynamic parameter identification (DPI) of the systems is required for optimal performance of the model-based controller. Current DPI methods are more suitable for systems with continuous dynamics. If any type of discontinuity (e.g., backlash) is present in the system, the DPI may have numerical problems for convergence. In this work, we propose a modified homotopy optimization to identify parameters of a system with mechanical discontinuity (i.e., backlash). The performance of the proposed method was first evaluated through a computer simulation on a system with sandwiched backlash. Results of the DPI showed that the proposed homotopy optimization can identify the discontinuous system parameters with a good accuracy. It was found that ignoring the backlash in the system dynamics imposes large errors in the system DPI. After verifying the proposed method using computer simulations, the DPI was implemented to identify the parameters of a rehabilitation robot with actuator backlash. The proposed method provided a better estimate of the system parameters compared to the no-backlash DPI of the experimental robot. Despite the noise in velocity and acceleration due to the numerical differentiation of the sampled angle measurements, the forward dynamics results are quite accurate for all of the tested configurations with the discontinuous backlash model.

@article{zhou_2018,
title = {A Multi-Time-Scale Finite Time Controller for the Quadrotor UAVs with Uncertainties},
author = {Zhou, Z.; Wang, H.; Hu, Z.; Wang, Y.; Wang, H.},
journal = {Journal of Intelligent & Robotic Systems},
year = {2018},
institution = {Yanshan University, China},
abstract = {A control method with a multi-time-scale structure is proposed to perform finite time motion control of the quadrotor unmanned aerial vehicles (UAVs) with uncertainties. In order to facilitate the controller-design, finite time extended state observer (ESO) in the first and second time scales is applied to estimate the system uncertainties; the attitude controllers and the height controller are designed for finite time stabilization of the equilibriums in the third time scale; and finally, the output feedback technique is utilized to design the horizontal auxiliary controllers, meanwhile the reference angles are settled for the attitude dynamics in the fourth and slowest time scale. It allows us to analyze the system dynamics in each time scale independently, and conclusions on finite time stabilization are achieved gradually with a large region of attraction. Simulation and experimental results on the Qball2 platform are given to verify the efficacy of the strategy and establish the feasibility of implementation. },
issn = {0921-0296},
keywords = {Finite time control, Extended state observer, Multi-time-scale, System uncertainties, Quadrotor UAVs},
language = {English},
publisher = {Springer Netherlands}
}

A control method with a multi-time-scale structure is proposed to perform finite time motion control of the quadrotor unmanned aerial vehicles (UAVs) with uncertainties. In order to facilitate the controller-design, finite time extended state observer (ESO) in the first and second time scales is applied to estimate the system uncertainties; the attitude controllers and the height controller are designed for finite time stabilization of the equilibriums in the third time scale; and finally, the output feedback technique is utilized to design the horizontal auxiliary controllers, meanwhile the reference angles are settled for the attitude dynamics in the fourth and slowest time scale. It allows us to analyze the system dynamics in each time scale independently, and conclusions on finite time stabilization are achieved gradually with a large region of attraction. Simulation and experimental results on the Qball2 platform are given to verify the efficacy of the strategy and establish the feasibility of implementation.

@article{sadala_2018,
title = {A new continuous sliding mode control approach with actuator saturation for control of 2-DOF helicopter system},
author = {Sadala, S.P.; Patre, B.M.},
journal = {ISA Transactions},
year = {2018},
institution = {Shri Guru Gobind Singhji Institute of Engineering and Technology, India},
abstract = {The 2-degree of freedom (DOF) helicopter system is a typical higher-order, multi-variable, nonlinear and strong coupled control system. The helicopter dynamics also includes parametric uncertainties and is subject to unknown external disturbances. Such complicated system requires designing a sophisticated control algorithm that can handle these difficulties. This paper presents a new robust control algorithm which is a combination of two continuous control techniques, composite nonlinear feedback (CNF) and super-twisting control (STC) methods. In the existing integral sliding mode (ISM) based CNF control law, the discontinuous term exhibits chattering which is not desirable for many practical applications. As the continuity of well known STC reduces chattering in the system, the proposed strategy is beneficial over the current ISM based CNF control law which has a discontinuous term. Two controllers with integral sliding surface are designed to control the position of the pitch and the yaw angles of the 2- DOF helicopter. The adequacy of this specific combination has been exhibited through general analysis, simulation and experimental results of 2-DOF helicopter setup. The acquired results demonstrate the good execution of the proposed controller regarding stabilization, following reference input without overshoot against actuator saturation and robustness concerning to the limited matched disturbances. },
keywords = {Composite nonlinear feedback (CNF) Actuator saturation 2-DOF helicopter Siding mode control (SMC) Integral sliding mode control (ISMC) Super-twisting control (STC)},
language = {English},
publisher = {Elsevier B.V.}
}

The 2-degree of freedom (DOF) helicopter system is a typical higher-order, multi-variable, nonlinear and strong coupled control system. The helicopter dynamics also includes parametric uncertainties and is subject to unknown external disturbances. Such complicated system requires designing a sophisticated control algorithm that can handle these difficulties. This paper presents a new robust control algorithm which is a combination of two continuous control techniques, composite nonlinear feedback (CNF) and super-twisting control (STC) methods. In the existing integral sliding mode (ISM) based CNF control law, the discontinuous term exhibits chattering which is not desirable for many practical applications. As the continuity of well known STC reduces chattering in the system, the proposed strategy is beneficial over the current ISM based CNF control law which has a discontinuous term. Two controllers with integral sliding surface are designed to control the position of the pitch and the yaw angles of the 2- DOF helicopter. The adequacy of this specific combination has been exhibited through general analysis, simulation and experimental results of 2-DOF helicopter setup. The acquired results demonstrate the good execution of the proposed controller regarding stabilization, following reference input without overshoot against actuator saturation and robustness concerning to the limited matched disturbances.

@conference{frazelle_2018,
title = {A Nonlinear Control Strategy for Extensible Continuum Robots},
author = {Frazelle, C.G.; Kapadia, A.D.; Walker, I.D.},
booktitle = {2018 IEEE International Conference on Robotics and Automation (ICRA)},
year = {2018},
institution = {Clemson University, USA},
abstract = {In this paper, we describe a novel nonlinear control strategy for the closed-loop control of extensible continuum robots. Previous attempts at controlling continuum robots have proved difficult due to the complexity of their system dynamics. Taking advantage of a previously developed dynamic model for a three-section, planar, continuum manipulator, we develop an adaptation-based control law. We present simulation results of a set-point tracking between a rigid-link control device and an extensible continuum manipulator. Experimental results of the controller implemented on a six degree-of-freedom continuum robot are also presented. },
issn = {2577-087X },
keywords = {closed loop systems, control system synthesis, manipulators, nonlinear control systems, PD control, variable structure systems},
language = {English},
publisher = {IEEE},
isbn = {978-1-5386-3082-2}
}

In this paper, we describe a novel nonlinear control strategy for the closed-loop control of extensible continuum robots. Previous attempts at controlling continuum robots have proved difficult due to the complexity of their system dynamics. Taking advantage of a previously developed dynamic model for a three-section, planar, continuum manipulator, we develop an adaptation-based control law. We present simulation results of a set-point tracking between a rigid-link control device and an extensible continuum manipulator. Experimental results of the controller implemented on a six degree-of-freedom continuum robot are also presented.

@article{Khadraoui_2018,
title = {A Nonparametric Approach to Design Fixed-order Controllers for Systems with Constrained Input},
author = {Khadraoui, S.; Nounou, H.},
journal = {International Journal of Control, Automation and Systems},
year = {2018},
volume = {16},
number = {6},
institution = {University of Sharjah, UAE; Texas A&M University at Qatar, Qatar},
abstract = {This paper presents an approach for designing fixed-structure controllers for input-constrained linear systems using frequency domain data. In conventional control approaches, a plant model is needed to design a suitable controller that meets some user-specified performance specifications. Mathematical models can be built based on fundamental laws or from a set of measurements. In both cases, it is difficult to find a simple and reliable model that completely describes the system behavior. Hence, errors associated with the plant modeling stage may contribute to the degradation of the desired closed-loop performance. Due to the fact that the modeling stage can be viewed only as an intermediate step introduced for the controller design, the concept of data-based control design has been introduced, where controllers are directly designed from measurements. Most existing data-based control approaches are developed for linear systems, which limit their application to systems with nonlinear phenomena. An important non-smooth nonlinearity observed in practical applications is the input saturation, which usually limits the system performance. Here, we attempt to develop a nonparametric approach to design controllers from frequency-domain data by taking into account input constraints. Two practical applications of the proposed method are presented to demonstrate its efficacy. },
issn = {1598-6446},
keywords = {Actuator saturation, constrained optimization, data-based control, frequency response, energy consumption, safe process operation},
language = {English},
publisher = {Springer Nature Switzerland},
pages = {2870-2877}
}

This paper presents an approach for designing fixed-structure controllers for input-constrained linear systems using frequency domain data. In conventional control approaches, a plant model is needed to design a suitable controller that meets some user-specified performance specifications. Mathematical models can be built based on fundamental laws or from a set of measurements. In both cases, it is difficult to find a simple and reliable model that completely describes the system behavior. Hence, errors associated with the plant modeling stage may contribute to the degradation of the desired closed-loop performance. Due to the fact that the modeling stage can be viewed only as an intermediate step introduced for the controller design, the concept of data-based control design has been introduced, where controllers are directly designed from measurements. Most existing data-based control approaches are developed for linear systems, which limit their application to systems with nonlinear phenomena. An important non-smooth nonlinearity observed in practical applications is the input saturation, which usually limits the system performance. Here, we attempt to develop a nonparametric approach to design controllers from frequency-domain data by taking into account input constraints. Two practical applications of the proposed method are presented to demonstrate its efficacy.

@conference{xie_2018,
title = {A position estimation and control system for the quadrotor in GPS-deny situation based on FAST detection and optical flow},
author = {Xie, N.; Li, X.; Yu, Y.},
booktitle = {2018 33rd Youth Academic Annual Conference of Chinese Association of Automation (YAC)},
year = {2018},
institution = {University of Science and Technology Beijing, China},
abstract = {Position estimation based on vision system is essential for a UAV in the GPS-deny situation to realize the position control. However, in the practice, the hardware and software are not ideal for the UAV to carry when flying. Thus, this study is aiming at the problem of position estimation and control for a quadrotor UAV based on vision. Firstly, a position estimation algorithm based on vision is proposed, in which optical flow is used combining with FAST corner detection to ensure the real-time performance of the estimation in condition with limited loader. Meanwhile, a robust controller with nonlinear compensating input has been designed in this paper to deal with the position control for the quadrotor. A simulation is presented in this paper to verify the performance of the controller. Moreover, an experiment is also utilized in this paper to show that the method is practical and with high performance. },
keywords = {quadrotor UAV, optical flow, FAST detection, sliding model control, position estimation and control},
language = {English},
publisher = {IEEE},
isbn = {978-1-5386-7256-3 }
}

Position estimation based on vision system is essential for a UAV in the GPS-deny situation to realize the position control. However, in the practice, the hardware and software are not ideal for the UAV to carry when flying. Thus, this study is aiming at the problem of position estimation and control for a quadrotor UAV based on vision. Firstly, a position estimation algorithm based on vision is proposed, in which optical flow is used combining with FAST corner detection to ensure the real-time performance of the estimation in condition with limited loader. Meanwhile, a robust controller with nonlinear compensating input has been designed in this paper to deal with the position control for the quadrotor. A simulation is presented in this paper to verify the performance of the controller. Moreover, an experiment is also utilized in this paper to show that the method is practical and with high performance.

Interconnection and damping assignment passivity based control (IDA-PBC) is a method that has been developed to (asymptotically) stabilize nonlinear systems formulated in port-controlled Hamiltonian (PCH) structure. This method has gained increasing popularity and has been successfully applied to a wide range of dynamical systems. However, little is known about the robustness of this method in response to the effects of uncertainty which could result from disturbances, noises, and modeling errors. This paper explores the possibility of extending some energy shaping methods, taking into account the robustness aspects, with the aim of maintaining (asymptotic) stability of the system in the presence of perturbations which inevitably exist in any realistic applications. We propose constructive results on robust IDA-PBC controllers for underactuated mechanical systems that are quite commonly found in practice and have the most challenging control problems within this context. The proposed results extend some existing methods and provide a new framework that allows the implementation of integral and input-to-state stability controllers to underactuated mechanical system.

@conference{cukierman_2018,
title = {A Student-Centered Approach to Learning Mathematics and Physics in Engineering Freshmen Courses},
author = {Cukierman, U.R.; Silvestri, S.; Drangosch, J.; Perez Fernandez, D.; Aguero, M.; Gonzalez, M.; Gonzalez, C.; Dellepiane, P.},
booktitle = {WEEF-GEDC 2018},
year = {2018},
institution = {FRBA - UTN, Argentina},
abstract = {It is very well known that one of the most important reasons for abandonment in Engineering freshmen courses is the difficulty expressed by students for understanding very basic and essential Mathematics and Physics’ concepts. But this is not the only reason for such a problem, the other very important cause for students’ maladaptation during their first courses at the University, is the teacher-centered model which predominates in a clear majority of Higher Education courses. This paper will describe an ongoing experience which involves first, the development of small apps (learning objects) to be used in mobile devices by freshmen in Mathematics and Physics’ courses and, second, the research about its impact in terms of learning outcomes. This methodology implies a Student-Centered and Active Learning approach, as students learn at their own pace by interacting with the apps, not only during lecture hours but, especially, before arriving to School, thus implementing a “Flipped-Learning” methodology. We will also describe in this paper the very first promising results obtained during this year as well as lessons learned during the phase of the project developed during last year. },
keywords = {Student Centered Learning; Active Learning; Flipped Learning; Mobile Learning},
language = {English}
}

It is very well known that one of the most important reasons for abandonment in Engineering freshmen courses is the difficulty expressed by students for understanding very basic and essential Mathematics and Physics’ concepts. But this is not the only reason for such a problem, the other very important cause for students’ maladaptation during their first courses at the University, is the teacher-centered model which predominates in a clear majority of Higher Education courses. This paper will describe an ongoing experience which involves first, the development of small apps (learning objects) to be used in mobile devices by freshmen in Mathematics and Physics’ courses and, second, the research about its impact in terms of learning outcomes. This methodology implies a Student-Centered and Active Learning approach, as students learn at their own pace by interacting with the apps, not only during lecture hours but, especially, before arriving to School, thus implementing a “Flipped-Learning” methodology. We will also describe in this paper the very first promising results obtained during this year as well as lessons learned during the phase of the project developed during last year.

@article{jurado_2018,
title = {A wavelet neural control scheme for a quadrotor unmanned aerial vehicle},
author = {Jurado, F.; Lopez, S.},
journal = {Philosophical Transactions of the Royal Society of Mathematical, Physical and Engineering Sciences},
year = {2018},
volume = {376},
number = {2126},
institution = {Tecnológico Nacional de México, Mexico; Instituto Tecnológico de La Laguna, Mexico},
abstract = {Wavelets are designed to have compact support in both time and frequency, giving them the ability to represent a signal in the two-dimensional time–frequency plane. The Gaussian, the Mexican hat and the Morlet wavelets are crude wavelets that can be used only in continuous decomposition. The Morlet wavelet is complex-valued and suitable for feature extraction using the continuous wavelet transform. Continuous wavelets are favoured when high temporal and spectral resolution is required at all scales. In this paper, considering the properties from the Morlet wavelet and based on the structure of a recurrent high-order neural network model, a novel wavelet neural network structure, here called a recurrent Morlet wavelet neural network, is proposed in order to achieve a better identification of the behaviour of dynamic systems. The effectiveness of our proposal is explored through the design of a decentralized neural backstepping control scheme for a quadrotor unmanned aerial vehicle. The performance of the overall neural identification and control scheme is verified via simulation and real-time results. This article is part of the theme issue ‘Redundancy rules: the continuous wavelet transform comes of age’. },
keywords = {backstepping control, Morlet wavelet, quadrotor, recurrent wavelet neural network},
language = {English},
publisher = {The Royal Society Publishing}
}

Wavelets are designed to have compact support in both time and frequency, giving them the ability to represent a signal in the two-dimensional time–frequency plane. The Gaussian, the Mexican hat and the Morlet wavelets are crude wavelets that can be used only in continuous decomposition. The Morlet wavelet is complex-valued and suitable for feature extraction using the continuous wavelet transform. Continuous wavelets are favoured when high temporal and spectral resolution is required at all scales. In this paper, considering the properties from the Morlet wavelet and based on the structure of a recurrent high-order neural network model, a novel wavelet neural network structure, here called a recurrent Morlet wavelet neural network, is proposed in order to achieve a better identification of the behaviour of dynamic systems. The effectiveness of our proposal is explored through the design of a decentralized neural backstepping control scheme for a quadrotor unmanned aerial vehicle. The performance of the overall neural identification and control scheme is verified via simulation and real-time results.

This article is part of the theme issue ‘Redundancy rules: the continuous wavelet transform comes of age’.

@conference{cheon_2018,
title = {Acceleration Based Force Estimation in Series Elastic Actuator},
author = {Cheon, D.; Oh, S.},
booktitle = {IECON 2018 - 44th Annual Conference of the IEEE Industrial Electronics Society},
year = {2018},
institution = {DGIST, South Korea},
abstract = {With increasing of the needs to collaborate with humans throughout the industry fields, a series elastic actua-tor(SEA)has been developed which enable more compliance motion rather than conventional motor-based actuator. The device is equipped with spring inside, and it turns increased mechanical elasticity, allowing to react more flexibly to the external force, generated by external environments such as impact. In this point, it is important to measure well spring deflection. Encoder with a delivery mechanism such as the belts, the gear, and the wire is typically used for the purpose. The high-resolution encoder improves the performance of SEA, however, at the same time, it is expensive. To solve this problem, we proposed an estimating method for external force using acceleration sensor. In previous studies, external force observer using encoders were designed as a shape of the transfer function and state space. The performance of observer using acceleration sensor is compared to two previous algorithms. },
issn = {1553-572X },
keywords = {force estimation, series elastic actuator, acceleration, state observer},
language = {English},
publisher = {IEEE},
isbn = {978-1-5090-6685-8}
}

With increasing of the needs to collaborate with humans throughout the industry fields, a series elastic actua-tor(SEA)has been developed which enable more compliance motion rather than conventional motor-based actuator. The device is equipped with spring inside, and it turns increased mechanical elasticity, allowing to react more flexibly to the external force, generated by external environments such as impact. In this point, it is important to measure well spring deflection. Encoder with a delivery mechanism such as the belts, the gear, and the wire is typically used for the purpose. The high-resolution encoder improves the performance of SEA, however, at the same time, it is expensive. To solve this problem, we proposed an estimating method for external force using acceleration sensor. In previous studies, external force observer using encoders were designed as a shape of the transfer function and state space. The performance of observer using acceleration sensor is compared to two previous algorithms.

@article{bolat_2018,
title = {Active Control of a Small-Scale Wind Turbine Blade Containing Magnetorheological Fluid},
author = {Bolat, F.C.; Sivrioglu, S.},
journal = {Micromachines},
year = {2018},
volume = {9},
number = {2},
institution = {Bayburt University, Turkey; Gebze Technical University, Turkey},
abstract = {This research study proposes a new active control structure to suppress vibrations of a small-scale wind turbine blade filled with magnetorheological (MR) fluid and actuated by an electromagnet. The aluminum blade structure is manufactured using the SH3055 (Bergey Windpower Co. Inc., Norman, OK, USA) code numbered airfoil which is designed for use on small wind turbines. A dynamic interaction model between the MR fluid and the electromagnetic actuator is constructed to obtain a force relation. A detailed characterization study is presented for the proposed actuator to understand the nonlinear behavior of the electromagnetic force. A norm based multi-objective H2/H∞ controller is designed using the model of the elastic blade element. The H2/H∞ controller is experimentally implemented under the impact and steady state aerodynamic load conditions. The results of experiments show that the MR fluid- electromagnetic actuator is effective for suppressing vibrations of the blade structure. },
keywords = {active vibration control; elastic blade; magnetorheological fluid; robust control},
language = {English}
}

This research study proposes a new active control structure to suppress vibrations of a small-scale wind turbine blade filled with magnetorheological (MR) fluid and actuated by an electromagnet. The aluminum blade structure is manufactured using the SH3055 (Bergey Windpower Co. Inc., Norman, OK, USA) code numbered airfoil which is designed for use on small wind turbines. A dynamic interaction model between the MR fluid and the electromagnetic actuator is constructed to obtain a force relation. A detailed characterization study is presented for the proposed actuator to understand the nonlinear behavior of the electromagnetic force. A norm based multi-objective H2/H∞ controller is designed using the model of the elastic blade element. The H2/H∞ controller is experimentally implemented under the impact and steady state aerodynamic load conditions. The results of experiments show that the MR fluid- electromagnetic actuator is effective for suppressing vibrations of the blade structure.

@conference{yazdjerdi2_2018,
title = {Actuator Fault Tolerant Control in a Team of Mobile Robots},
author = {Yazdjerdi, P.; Meskin, N.},
booktitle = {2018 15th International Conference on Control, Automation, Robotics and Vision (ICARCV)},
year = {2018},
institution = {Qatar University, Doha, Qatar},
abstract = {In this paper, a fault tolerant controller is developed for loss of effectiveness actuator faults in differential drive mobile robots. Based on the extended Kalman filter technique, a joint parameter and state estimation method is used to estimate the actuator loss of effectiveness gains as the parameters of the system. The estimated gains are then used in the controller to compensate the effect of actuator faults. Moreover, a fault tolerant leader-follower controller is developed to control multiple robots moving on a desired trajectory in a formation in the presence of actuator faults in leader or followers. The proposed method is implemented on Qbot-2 and its performance is experimentally validated. },
keywords = {Fault tolerant control (FTC), Mobile robots, Extended Kalman filter, Loss of effectiveness actuator fault, Leader-Follower},
language = {English},
publisher = {IEEE},
isbn = {978-1-5386-9583-8 }
}

In this paper, a fault tolerant controller is developed for loss of effectiveness actuator faults in differential drive mobile robots. Based on the extended Kalman filter technique, a joint parameter and state estimation method is used to estimate the actuator loss of effectiveness gains as the parameters of the system. The estimated gains are then used in the controller to compensate the effect of actuator faults. Moreover, a fault tolerant leader-follower controller is developed to control multiple robots moving on a desired trajectory in a formation in the presence of actuator faults in leader or followers. The proposed method is implemented on Qbot-2 and its performance is experimentally validated.

@article{yan_2018,
title = {Adaptive Fault Detection and Isolation for Active Suspension Systems With Model Uncertainties},
author = {Yan, S.; Sun, W.; He, F.; Yao, J.},
journal = {IEEE Transactions on Reliability},
year = {2018},
institution = {Harbin Institute of Technology, China; Nanjing University of Science and Technology, China},
abstract = {Suspension operation reliability is one of the most significant performance indexes that concerns maneuvering stability and drive safety. In this paper, in order to guarantee good suspension reliability, an adaptive fault detection and isolation scheme is proposed for quarter-car active suspension systems with parametric and nonlinear uncertainties. To realize fault diagnosis for active suspensions, an adaptive fault detection estimator and several fault isolation estimators are designed to generate state residuals. Corresponding adaptive thresholds are developed to help judge the occurrence and type of possible faults. In the process of constructing state estimators, the uncertain parameter is updated online so that good sensitivity of fault detection can be achieved. Illustrative simulation is carried out to validate the effectiveness of the fault diagnosis scheme, and results indicate that the proposed method is sensible to sudden faults and maintain robustness to model uncertainties appearing in suspension systems. },
issn = {0018-9529 },
keywords = {Active suspension systems, fault detection, fault isolation, model uncertainties, parameter adaption},
language = {English},
publisher = {IEEE}
}

Suspension operation reliability is one of the most significant performance indexes that concerns maneuvering stability and drive safety. In this paper, in order to guarantee good suspension reliability, an adaptive fault detection and isolation scheme is proposed for quarter-car active suspension systems with parametric and nonlinear uncertainties. To realize fault diagnosis for active suspensions, an adaptive fault detection estimator and several fault isolation estimators are designed to generate state residuals. Corresponding adaptive thresholds are developed to help judge the occurrence and type of possible faults. In the process of constructing state estimators, the uncertain parameter is updated online so that good sensitivity of fault detection can be achieved. Illustrative simulation is carried out to validate the effectiveness of the fault diagnosis scheme, and results indicate that the proposed method is sensible to sudden faults and maintain robustness to model uncertainties appearing in suspension systems.

@article{das_2018,
title = {Adaptive Predator-Prey Optimization for Tuning of Infinite Horizon LQR applied to Vehicle Suspension System},
author = {Das, R.R.; Elumalai, V.K.; Subramanian, R.G.; Venkata, K.; Kumar, A.},
journal = {Applied Soft Computing},
year = {2018},
institution = {Eindhoven University of Technology, The Netherlands; VIT University, India; Larson and Toubro Limited, India},
abstract = {This paper puts forward an adaptive predator-prey optimization algorithm to solve the weight selection problem of linear quadratic control applied for vibration control of vehicle suspension system. The proposed technique addresses the two key issues of PSO, namely (a) the premature convergence of the particles, and (b) the imbalance between exploration and exploitation of the particles in finding the global optimum. The main principle behind this optimization algorithm is that the inertia weight is adaptively updated based on the success rate of the particles to increase the convergence, and the predator-prey strategy is reinforced to avoid the particles getting trapped in a local minimum thereby, guaranteeing convergence of the particles towards the global optimal solution. The convergence of the particles towards the global minimum is guaranteed on the basis of a passivity argument. Moreover, the strength of this new adaptive optimization technique to tune the gains of linear quadratic regulator is validated experimentally on a laboratory scale active vehicle suspension system for improved ride comfort and passenger safety. },
keywords = {LQR, Active Vehicle Suspension System, PSO, AIWF, Predator-Prey strategy},
language = {English},
publisher = {Elsevier B.V.}
}

This paper puts forward an adaptive predator-prey optimization algorithm to solve the weight selection problem of linear quadratic control applied for vibration control of vehicle suspension system. The proposed technique addresses the two key issues of PSO, namely (a) the premature convergence of the particles, and (b) the imbalance between exploration and exploitation of the particles in finding the global optimum. The main principle behind this optimization algorithm is that the inertia weight is adaptively updated based on the success rate of the particles to increase the convergence, and the predator-prey strategy is reinforced to avoid the particles getting trapped in a local minimum thereby, guaranteeing convergence of the particles towards the global optimal solution. The convergence of the particles towards the global minimum is guaranteed on the basis of a passivity argument. Moreover, the strength of this new adaptive optimization technique to tune the gains of linear quadratic regulator is validated experimentally on a laboratory scale active vehicle suspension system for improved ride comfort and passenger safety.

@article{merabet_2018,
title = {Adaptive Sliding Mode Speed Control for Wind Energy Experimental System},
author = {Merabet, A.},
journal = {Energies},
year = {2018},
volume = {11},
number = {9},
institution = {Saint Mary’s University, Canada},
abstract = {In this paper, an adaptive sliding mode speed control algorithm with an integral-operation sliding surface is proposed for a variable speed wind energy experimental system. In the control design, an estimator is designed to compensate for the uncertainties and the unknown turbine torque. In addition, the bound of the sliding mode is investigated to deal with uncertainties. The stability of the system can be guaranteed in the sense of the Lyapunov stability theorem. The laboratory size DC generator wind energy system is controlled using a buck-boost DC-DC converter interface. The control system is validated by experimentation and results demonstrate the achievement of favorable speed tracking performance and robustness against parametric variations and external disturbances. },
keywords = {adaptive control; sliding mode control; speed control; wind energy system},
language = {English},
publisher = {MDPI}
}

In this paper, an adaptive sliding mode speed control algorithm with an integral-operation sliding surface is proposed for a variable speed wind energy experimental system. In the control design, an estimator is designed to compensate for the uncertainties and the unknown turbine torque. In addition, the bound of the sliding mode is investigated to deal with uncertainties. The stability of the system can be guaranteed in the sense of the Lyapunov stability theorem. The laboratory size DC generator wind energy system is controlled using a buck-boost DC-DC converter interface. The control system is validated by experimentation and results demonstrate the achievement of favorable speed tracking performance and robustness against parametric variations and external disturbances.

@article{yang2_2018,
title = {Aerodynamic parameters identification and adaptive LADRC attitude control of quad-rotor model},
author = {Yang, S.; Xi, L.; Hao, J.; Zhao, Y.; Yang, Y.; Wang, W.},
year = {2018},
institution = {Army Engineering University, China; Beihang University, China; Shijiazhuang Tiedao University, China; China Aerodynamics Research and Development Center, China; University of Warwick, UK},
abstract = {In accordance with problems such as difficulty in obtaining aerodynamic parameters of a quad-rotor model, the change of model parameters with external interference affects the control performances, an aerodynamic parameter estimation method and an adaptive attitude control method based on LADRC are designed. Firstly, the motion model, dynamics model and control distribution model of quad-rotor are established by using the aerodynamic and Newtonian Euler equations. Secondly, the identification tool CIFER is used to identify the aerodynamic parameters with large uncertainties in frequency domain and a more accurate attitude model of the quad-rotor is obtained. Then an adaptive attitude decoupling controller based on LADRC is designed to solve the problem of poor anti-interference ability of the quad-rotor, so that the control parameter b0 can be automatically adjusted to identify the change of the moment of inertia in real time. Finally, a semi-physical simulation platform is used for simulation verification. The results show that the adaptive LADRC attitude controller designed can effectively estimate and compensate the system's internal and external disturbances, and the tracking speed of the controller is faster and the precision is higher which can effectively improve system's anti-interference and robustness. },
keywords = {Quad-rotor; Parameters identification; CIFER; Adaptive LADRC},
language = {English}
}

In accordance with problems such as difficulty in obtaining aerodynamic parameters of a quad-rotor model, the change of model parameters with external interference affects the control performances, an aerodynamic parameter estimation method and an adaptive attitude control method based on LADRC are designed. Firstly, the motion model, dynamics model and control distribution model of quad-rotor are established by using the aerodynamic and Newtonian Euler equations. Secondly, the identification tool CIFER is used to identify the aerodynamic parameters with large uncertainties in frequency domain and a more accurate attitude model of the quad-rotor is obtained. Then an adaptive attitude decoupling controller based on LADRC is designed to solve the problem of poor anti-interference ability of the quad-rotor, so that the control parameter b0 can be automatically adjusted to identify the change of the moment of inertia in real time. Finally, a semi-physical simulation platform is used for simulation verification. The results show that the adaptive LADRC attitude controller designed can effectively estimate and compensate the system's internal and external disturbances, and the tracking speed of the controller is faster and the precision is higher which can effectively improve system's anti-interference and robustness.

@article{riviere_2018,
title = {Agile Robotic Fliers: A Morphing-Based Approach},
author = {Riviere, V.; Manecy, A.; Viollet, S.},
journal = {Soft Robotics},
year = {2018},
institution = {Aix Marseille University, France; ONERA Midi-Pyrenees Toulouse Center, France},
abstract = {The aerial robot presented here for the first time was based on a quadrotor structure, which is capable of unique morphing performances based on an actuated elastic mechanism. Like birds, which are able to negotiate narrow apertures despite their relatively large wingspan, our Quad-Morphing robot was able to pass through a narrow gap at a high forward speed of 2.5 m.s−1 by swiftly folding up the structure supporting its propellers. A control strategy was developed to deal with the loss of controllability on the roll axis resulting from the folding process, while keeping the robot stable until it has crossed the gap. In addition, a complete recovery procedure was also implemented to stabilize the robot after the unfolding process. A new metric was also used to quantify the gain in terms of the gap-crossing ability in comparison with that observed with classical quadrotors with rigid bodies. The performances of these morphing robots are presented, and experiments performed with a real flying robot passing through a small aperture by reducing its wingspan by 48% are described and discussed. },
keywords = {morphing robot, quadrotors, obstacle avoidance, bioinspired, aerial robot, elastic folding mechanism},
language = {English},
publisher = {Mary Ann Liebert, Inc.}
}

The aerial robot presented here for the first time was based on a quadrotor structure, which is capable of unique morphing performances based on an actuated elastic mechanism. Like birds, which are able to negotiate narrow apertures despite their relatively large wingspan, our Quad-Morphing robot was able to pass through a narrow gap at a high forward speed of 2.5 m.s−1 by swiftly folding up the structure supporting its propellers. A control strategy was developed to deal with the loss of controllability on the roll axis resulting from the folding process, while keeping the robot stable until it has crossed the gap. In addition, a complete recovery procedure was also implemented to stabilize the robot after the unfolding process. A new metric was also used to quantify the gain in terms of the gap-crossing ability in comparison with that observed with classical quadrotors with rigid bodies. The performances of these morphing robots are presented, and experiments performed with a real flying robot passing through a small aperture by reducing its wingspan by 48% are described and discussed.

@article{oksuz_2018,
title = {Alternative Controller Design for Rotary Inverted Pendulum},
author = {Oksuz, M.; Onal, M.B.; Halicioglu, R.; Dulger, L.C.},
journal = {Tehnicki Glasnik},
year = {2018},
volume = {12},
number = {3},
institution = {Turkish Aeronautical Association University, Turkey; İzmir University of Economics, Turkey},
abstract = {The inverted pendulum has been considered a classical control problem. Two designs of inverted pendulum are planar and rotary with a nonlinear unstable system characteristic. Inverted pendulum systems are nonlinear. They can be used for testing and studying various observers and controllers. Control of a rotary inverted pendulum is studied here. This paper proposes stabilization of the rotary inverted pendulum at its upright position by using full-state controller. Full-state controllers are designed by using different damping ratios. MATLAB simulation results and the experimental results are taken for 10 degrees step for 5 seconds. The best controller is chosen for SRV02-Rotary inverted pendulum by looking at the simulation and experimental results. },
keywords = {controller design; full-state controller; linearization; pole placement; rotary inverted pendulum (RIP); stabilization},
language = {English},
pages = {139-145}
}

The inverted pendulum has been considered a classical control problem. Two designs of inverted pendulum are planar and rotary with a nonlinear unstable system characteristic. Inverted pendulum systems are nonlinear. They can be used for testing and studying various observers and controllers. Control of a rotary inverted pendulum is studied here. This paper proposes stabilization of the rotary inverted pendulum at its upright position by using full-state controller. Full-state controllers are designed by using different damping ratios. MATLAB simulation results and the experimental results are taken for 10 degrees step for 5 seconds. The best controller is chosen for SRV02-Rotary inverted pendulum by looking at the simulation and experimental results.

@conference{abdullah2_2018,
title = {Alternative Method for Predictive Functional Control to Handle an Integrating Process},
author = {Abdullah, M.; Rossiter, J.A.},
booktitle = {Control 2018 - 12th UKACC International Conference on Control},
year = {2018},
institution = {University of Sheffield, UK; International Islamic University Malaysia, Malaysia},
abstract = {This work proposes an improved method for Predictive Functional Control (PFC) to handle an integrating process. Instead of assuming a constant future input, the dynamic is shaped with a first-order Laguerre polynomial so that it converges to the expected steady state value. This modification provides simpler coding and tuning compared to the conventional method in the literature. Simulation results show that the proposed controller improves the consistency of the open-loop prediction of an integrating process and thus improves closed-loop performance and constraint handling properties. The practicality of this algorithm is also validated on laboratory hardware. },
keywords = {Predictive Control, PFC, Laguerre Function, Constraints, Integrating Process, Transparent Control, Servo System},
language = {English},
publisher = {IEEE}
}

This work proposes an improved method for Predictive Functional Control (PFC) to handle an integrating process. Instead of assuming a constant future input, the dynamic is shaped with a first-order Laguerre polynomial so that it converges to the expected steady state value. This modification provides simpler coding and tuning compared to the conventional method in the literature. Simulation results show that the proposed controller improves the consistency of the open-loop prediction of an integrating process and thus improves closed-loop performance and constraint handling properties. The practicality of this algorithm is also validated on laboratory
hardware.

@article{marquez-sanchez_2018,
title = {An Embedded Hardware for Implementation of a Tracking Control in WMRs},
author = {Sanchez, C.M.; Ortiga, R.S.; Sanchez, J.R.G.; Guzman, V.M.H.; Cruz, M.A., Aranda, M.M.; Ortigoza, G.S.},
journal = {IEEE Latin America Transactions},
year = {2018},
month = {07},
volume = {16},
number = {7},
institution = {IPN Mexico; Universidad Autónoma de Querétaro, Mexico; Universidad Autónoma de Puebla, Mexico},
abstract = {The implementation of a hierarchical controller for the trajectory tracking control of a wheeled mobile robot (WMR) is presented in this work. The experimental development of such a controller is performed with the low-cost embedded hardware Jetson TK1 from NVIDIA. In the programming of the controller, free license software with short learning curve is used. To validate the performance of the embedded hardware, a comparison between the results obtained from the WMR in closed-loop is presented when using: a) the embedded hardware Jetson TK1 and b) the fast prototyping DS1104 board from dSPACE. The experimental results show that the Jetson TK1 board could be suitable for the control of autonomous mechatronic systems. },
issn = {1548-0992 },
keywords = {DS1104, Embedded hardware, Hierarchical controller, Jetson TK1, Trajectory tracking, Wheeled mobile robot},
language = {Spanish},
publisher = {IEEE},
pages = {1835 - 1842}
}

The implementation of a hierarchical controller for the trajectory tracking control of a wheeled mobile robot (WMR) is presented in this work. The experimental development of such a controller is performed with the low-cost embedded hardware Jetson TK1 from NVIDIA. In the programming of the controller, free license software with short learning curve is used. To validate the performance of the embedded hardware, a comparison between the results obtained from the WMR in closed-loop is presented when using: a) the embedded hardware Jetson TK1 and b) the fast prototyping DS1104 board from dSPACE. The experimental results show that the Jetson TK1 board could be suitable for the control of autonomous mechatronic systems.

@article{li_2018,
title = {An Enhanced IBVS Controller of a 6DOF Manipulator Using Hybrid PDSMC Method},
author = {Li, S.; Ghasemi, A.; Xie, W.; Gao, Y.},
journal = {International Journal of Control, Automation and Systems},
year = {2018},
month = {04},
volume = {16},
number = {2},
institution = {Harbin Engineering University, China; Concordia University, Canada},
abstract = {The accuracy and stability are two fundamental concerns of the visual servoing control system. This paper presents an enhanced image based visual servoing (IBVS) method for increasing the accuracy of a 6DOF manipulator. The controller is designed to combine proportional derivative (PD) control with sliding mode control (SMC) on a 6DOF manipulator. The properly tuned PD controller can ensure the fast tracking performance and SMC can deal with the external disturbance and uncertainties due to the depth. The enhanced IBVS controller benefits from simple structure and easy implementation of PD control and good robustness to uncertainties of SMC. The stability of the proposed method is proven by using Lyapunov method. Simulation and experimental results are used to demonstrate the effectiveness of the proposed controller. },
issn = {1598-6446},
keywords = {Image based visual servoing (IBVS), PD control, sliding mode control, 6DOF manipulator},
language = {English},
publisher = {Springer},
pages = {844-855}
}

The accuracy and stability are two fundamental concerns of the visual servoing control system. This paper presents an enhanced image based visual servoing (IBVS) method for increasing the accuracy of a 6DOF manipulator. The controller is designed to combine proportional derivative (PD) control with sliding mode control (SMC) on a 6DOF manipulator. The properly tuned PD controller can ensure the fast tracking performance and SMC can deal with the external disturbance and uncertainties due to the depth. The enhanced IBVS controller benefits from simple structure and easy implementation of PD control and good robustness to uncertainties of SMC. The stability of the proposed method is proven by using Lyapunov method. Simulation and experimental results are used to demonstrate the effectiveness of the proposed controller.

@article{hernandez-perez_2018,
title = {An improvement on the PI controller for a class of high-order unstable delayed systems: Application to a thermal process},
author = {Hernandez-Perez, M.A.; del Muro-Cuellar, B.; Velasco-Villa, M.; Novella-Rodriguez, D.F.; Garrido-Moctezuma, R.A.; Garcia-Ramirez, P.J.},
journal = {Control Engineering and Applied Informatics},
year = {2018},
volume = {20},
number = {1},
institution = {Universidad Veracruzana, Mexico; Instituto Politécnico Nacional, Mexico; CINVESTAV-IPN, Mexico},
abstract = {This work addresses the stabilization and control problem of a class of input-output delayed unstable linear systems, i.e. n -order systems with one unstable pole and possibly one minimum phase zero. The problem is solved employing a modified version of the traditional PI, called the PIf controller, which incorporates a low-pass first order filter. This new scheme allows improving the existing results using the PI controller for high-order systems with time delay. The proposed control strategy is experimentally assessed through the temperature control of an unstable heat flow process. },
keywords = {Linear Systems, time–delay, modified PI control, unstable process, thermal process},
language = {English}
}

This work addresses the stabilization and control problem of a class of input-output delayed unstable linear systems, i.e. n -order systems with one unstable pole and possibly one minimum phase zero. The problem is solved employing a modified version of the traditional PI, called the PIf controller, which incorporates a low-pass first order filter. This new scheme allows improving the existing results using the PI controller for high-order systems with time delay. The proposed control strategy is experimentally assessed through the temperature control of an unstable heat flow process.

Plant-wide control implies advanced supervisory algorithms to maintain desired performance in the involved coupled sub-systems. The dynamical interactions among these sub-systems can vary with the operating point, material properties and disturbances present in the process. Recirculating loops introduce additional phenomena in the dynamic response, further challenging the control tasks. Complex process dynamics may be linear parameter varying (LPV) and may be difficult, if not impossible, to identify properly. In this context, maintaining global performance is a challenge one must undertake with limited information at hand. This paper investigates the trade-off between the complexity of the implementation and achieved performance, using supervisory predictive control with limited information shared, applied on a test-bench representative for process control industry. The robustness of the proposed algorithms is tested against a nominal scenario in which the prediction model is fully identified, with complete information exchange. Experimental tests are performed on a test-bench process characterized by strong interactions, and the results illustrate the usefulness of this work.