As a data-driven design method, model-free optimal control based on reinforcement learning provides an effective way to find optimal control strategies. The design of model-free optimal control is sensitive to system data because it relies on data rather than detailed dynamic models. A prerequisite for generating applicable data is that the system must be open-loop stable (with a stable equilibrium point), which restricts the data-based control design methods in actual control problems and leads to rare experimental studies or verification in the literature. To improve this situation and enrich its applications, we propose a pre-stabilized mechanism and apply it to the motion control of a mechanical system together with a reinforcement learning-based model-free optimal control method, which constitutes a so-called hierarchical control structure. We design two real-time control experiments on an underactuated system to verify its effectiveness. The control results show that the proposed hierarchical control is quite promising in controlling this mechanical system, even though it is open-loop unstable with unknown dynamics.

This study presents feedback linearization (FL)-based robust control for flexible joint robotic system under uncertain conditions. Robust control is achieved by designing the proportional integral observer (PIO). Modern control design typically has two requirements, namely (1) a complete state vector for their implementation and (2) the estimation of uncertain states. However, above mentioned requirements are difficult to meet in a real life systems. The FL-based controller design requires the complete knowledge about all the states of the system. The design also necessitates accurate understanding of system model, rendering controller performance sensitive to uncertainties. The efficiency of the proposed FL controller deteriorates in the presence of modelling uncertainties and their implementation necessitates the use of the complete transformed state vector. To fulfil aforementioned requirements, this work presents a design of a FL-based PIO that estimates both the state vector and the uncertainties including modelling error, parameter variation and external disturbances acting on the system simultaneously. The proposed observer-based controller structure is established and closed-loop stability proved. Simulations show the effectiveness of the PIO in estimating states and uncertainties, as well as the performance of the FL+PIO controller in tracking. Finally, the efficacy of suggested method is proved by experimental validation using Quanser flexible joint module.

Experiences in managing hands-on laboratory activ-ities across five different Electrical and Computer Engineering courses or subjects in three different Australian universities during the COVID-19 pandemic are presented. With different financial, logistical and other resource constraints and lock down conditions in different state jurisdictions, a multitude of approaches were used which included: at-home labs with hardware kits posted by teaching coordinators or acquired directly from suppliers by students; remote tutor interactions; remote test-bed; remote and cloud-based assessments; and remotely accessed and manipulated lab equipment. This paper aims to share experience in maintaining hands-on learning objectives intact during mostly online teaching while providing lessons learnt and qualitative comparisons among different approaches utilised.

Performance evaluation of trajectory tracking for a rotary flexible joint system is demonstrated in this paper. The robust and converse dynamic (RCD) technique is proposed and implemented for this evaluation. This control methodology is of the left inversion type, i.e., the control inputs are obtained by means of plant output error feedback. RCD control encompasses the baseline inverse (BI) control and sliding mode control-based discontinuous control element. The baseline inverse controller enforces the prescribed servo (virtual) constraints that represent the control objectives. The control objectives of the baseline inverse controller are enclosed in the form of servo (virtual) constraints which are inverted using Moore–Penrose Generalized Inverse (MPGI) to solve for the baseline control law. To boost the robust attributes against parametric uncertainties and disturbances, a discontinuous control function is augmented with baseline controller such that semiglobal practical stability is guaranteed in the sense of Lyapunov. To exhibit the effectiveness of RCD control in terms of tracking performance, computer simulations are conducted in Simulink/Matlab environment. Furthermore, the practical implementation is also investigated through a real-time experiment on Quanser’s rotary flexible joint manipulator system. The experimental results obtained by RCD are compared to the conventional sliding mode and fractional-order control techniques.

This paper proposes a technique to identify nonlinear dynamical systems with time delay. The sparse optimization algorithm is extended to nonlinear systems with time delay. The proposed algorithm combines cross-validation techniques from machine learning for automatic model selection and an algebraic operation for preprocessing signals to filter the noise and for removing the dependence on initial conditions. We further integrate the bootstrapping resampling technique with the sparse regression to obtain the statistical properties of estimation. We use Taylor expansion to parameterize time delay. The proposed algorithm in this paper is computationally efficient and robust to noise. A nonlinear Duffing oscillator is simulated to demonstrate the efficiency and accuracy of the proposed technique. An experimental example of a nonlinear rotary flexible joint is presented to further validate the proposed method.

In this work, considering some important indices such as speed of the system response, control effort with minimum error and vibrations of the flexible joint manipulator system combining them into an objective function, an optimization problem is defined in order to find the optimal weighting matrices Q and R in LQR controller. To solve this optimization problem, intelligent optimization technique such as Particle Swarm Optimization (PSO) is used. PSO is applied to flexible joint manipulator to enhance the performance of the controller and optimally adjusting the weighting matrices Q and R matrix in LQR controller. The response obtained for manually tuned by hit and trial and LQR tuned by PSO are compared in terms of time domain characteristics. Effectiveness and optimal response of the proposed controller are achieved on Matlab/simulink.

This paper presents an adaptive generalized dynamic inversion (AGDI) control methodology to the problem of angular position tracking of the rotary flexible joint system while suppressing joint vibrations. The AGDI control is composed of an equivalent control, which is responsible to enforce the prescribed constraint dynamics that encompasses the control objectives and control expression is obtained by inverting the constraint dynamics using Moore–Penrose generalized inversion. Furthermore, robustness is achieved by integrating a switching (discontinuous) term based on the sliding mode control method. The sliding mode gain of the switching control law is made adaptive for chattering reduction and improved tracking capability. The performance of AGDI control is evaluated through both numerical simulation and experimental investigations executed on Quanser's rotary flexible joint system. Simulation and experimental results reveal that the AGDI control is quiet capable to achieve the desired response curves against set-point tracking and disturbance rejection scenarios.

In this paper, an adaptive fuzzy generalized predictive controller is proposed for the anti-chaos control where the system dynamics are assumed to be unknown or uncertain in large. In the proposed mechanism, the control signal is generated by an input constraint generalized predictive controller to track the Duffing oscillator which is used as a chaotic reference system. The adaptive fuzzy system, as a real plant model, is employed to obtain prediction through the receding horizon. In order to show the capability of the proposed mechanism, three different payloads and noise cases are studied in the real-time control experiments of flexible-joint manipulator and tracking results are compared with three more non-model-based controllers which are conventional adaptive fuzzy control, indirect adaptive fuzzy sliding mode controller and proportional–integrative–derivative control. Results show that the proposed mechanism has better control performance than the others.

@conference{halverson_2020,
title = {Attitude Control of a Spacecraft Flexible Appendage using Parallel Feedforward Control},
author = {Halverson, R.D.; Caverly, R.},
booktitle = {AIAA Scitech 2020 Forum},
year = {2020},
institution = {University of Minnesota, USA},
abstract = {In this paper, static and dynamic strictly positive real (SPR) parallel feedforward control methods are applied to a spacecraft with a large payload attached to the end of a flexible appendage. A dynamic model of this spacecraft is considered with a torque applied directly to the hub of the spacecraft, where the control objective is to track a desired angular velocity of the payload. This setup leads to a noncolocated relationship between the spacecraft hub torque input and the payload angular velocity output. Numerical simulation results demonstrate that the parallel feedforward controller successfully renders the system SPR, which simplifies the choice of a stabilizing feedback controller. It is shown that parallel feedforward control significantly increases the effective gain of the feedback controller within a specified frequency bandwidth. These results are expanded to an experimental rotary flexible joint manipulator, which is used as a physical analog to the flexible-appendage spacecraft. The experimental results confirm the findings from the numerical results, demonstrating the practical nature of the proposed control method. Both numerical and experimental results include a comparison to the state-of-the-art mu-tip control method that relies on a massive payload assumption, where it is shown that parallel feedforward control is implementable in situations where mu-tip control is not. },
language = {English},
publisher = {AIAA}
}

In this paper, static and dynamic strictly positive real (SPR) parallel feedforward control methods are applied to a spacecraft with a large payload attached to the end of a flexible appendage. A dynamic model of this spacecraft is considered with a torque applied directly to the hub of the spacecraft, where the control objective is to track a desired angular velocity of the payload. This setup leads to a noncolocated relationship between the spacecraft hub torque input and the payload angular velocity output. Numerical simulation results demonstrate that the parallel feedforward controller successfully renders the system SPR, which simplifies the choice of a stabilizing feedback controller. It is shown that parallel feedforward control significantly increases the effective gain of the feedback controller within a specified frequency bandwidth. These results are expanded to an experimental rotary flexible joint manipulator, which is used as a physical analog to the flexible-appendage spacecraft. The experimental results confirm the findings from the numerical results, demonstrating the practical nature of the proposed control method. Both numerical and experimental results include a comparison to the state-of-the-art mu-tip control method that relies on a massive payload assumption, where it is shown that parallel feedforward control is implementable in situations where mu-tip control is not.

@article{rsetam_2020,
title = {Cascaded Extended State Observer Based Sliding Mode Control for Underactuated Flexible Joint Robot},
author = {Rsetam, K.A.; Cao, Z.; Man, Z.},
journal = {IEEE Transactions on Industrial Electronics},
year = {2020},
institution = {Swinburne University of Technology, Australia},
abstract = {This paper presents a new cascaded extended state observer (CESO) based sliding mode control (SMC) for an underactuated flexible joint robot (FJR). The control of FJR has many challenges including coupling, underactuation, nonlinearity, uncertainties and external disturbances, and the noise amplification especially in the high order systems. The proposed control integrates CESO and SMC, in which the CESO estimates the states and disturbances, and the SMC provides the system robustness to the uncertainty and disturbance estimation errors. Firstly, a dynamic model of the FJR is derived and converted from an underactuated form to a canonical form via the Olfati transformation and flatness approach, which reduces the complexity of the controller design. Furthermore, by taking the advantage of available measurable states, the CESO is adopted to attenuate the noises and make SMC feasible for high order systems. Moreover, the CESO estimates the disturbances, which relaxes the upper bound of the disturbance in the SMC and reduces the chattering due to smaller switching gains. A stability analysis of the closed loop system is presented based on the Lyapunov method. The effectiveness of the proposed control is verified experimentally on a real time FJR system. },
issn = {1557-9948},
keywords = {Flexible Joint Robot (FJR), underactuation, cascade extended state observer (CESO), sliding mode Control (SMC)},
language = {English},
publisher = {IEEE}
}

This paper presents a new cascaded extended state observer (CESO) based sliding mode control (SMC) for an underactuated flexible joint robot (FJR). The control of FJR has many challenges including coupling, underactuation, nonlinearity, uncertainties and external disturbances, and the noise amplification especially in the high order systems. The proposed control integrates CESO and SMC, in which the CESO estimates the states and disturbances, and the SMC provides the system robustness to the uncertainty and disturbance estimation errors. Firstly, a dynamic model of the FJR is derived and converted from an underactuated form to a canonical form via the Olfati transformation and flatness approach, which reduces the complexity of the controller design. Furthermore, by taking the advantage of available measurable states, the CESO is adopted to attenuate the noises and make SMC feasible for high order systems. Moreover, the CESO estimates the disturbances, which relaxes the upper bound of the disturbance in the SMC and reduces the chattering due to smaller switching gains. A stability analysis of the closed loop system is presented based on the Lyapunov method. The effectiveness of the proposed control is verified experimentally on a real time FJR system.

@article{kong_2020,
title = {Contraction analysis of nonlinear noncausal iterative learning control},
author = {Kong, F.H.; Manchester, I.R.},
journal = {Systems & Control Letters},
year = {2020},
month = {02},
volume = {136},
institution = {Universty of Sydney, Australia},
abstract = {Iterative learning control (ILC) is a method for learning input signals for repetitive control tasks. In this paper, we provide a new method based on convex optimization for certifying convergence and estimating convergence rate in ILC schemes involving a nonlinear plant and a noncausal update law, which are common in practice. Using sum-of-squares (SOS) optimization, we compute the convergence rate of an example nonlinear, noncausal ILC system and verify its accuracy in experiment. },
keywords = {Iterative learning control, Contraction analysis, Linear matrix inequalities},
language = {English},
publisher = {Elsevier B.V.}
}

Iterative learning control (ILC) is a method for learning input signals for repetitive control tasks. In this paper, we provide a new method based on convex optimization for certifying convergence and estimating convergence rate in ILC schemes involving a nonlinear plant and a noncausal update law, which are common in practice. Using sum-of-squares (SOS) optimization, we compute the convergence rate of an example nonlinear, noncausal ILC system and verify its accuracy in experiment.

This paper presents the Reinforcement Learning (RL) technique for control of a Flexible Joint Experiment. In the firs part of the paper an overview of the field of Reinforcement Learning in the frame of Machine Learning context and some basic RL strategies for control are highlighted. The design of RL controllers for linear systems is briefly presented. The RL based on two neural networks is designed for an experiment that consists of a DC motor and a rigid beam with flexible joint. The goal of the control system is that the beam tap to follow a predefined trajectory. The experimental setup is a nonlinear system, but in order to tune the controller parameters, a linear model is derived. The controller performances are evaluated using a real plant experiment. In the last sections of the paper the results obtained by numerical simulation and the main conclusions regarding the performance of the control system are presented.

@article{zhao5_2020,
title = {Online Probabilistic Estimation of Sensor Faulty Signal in Industrial Processes and Its Applications},
author = {Zhao, S.; Huang, B.; Zhao, C.},
journal = {IEEE Transactions on Industrial Electronics},
year = {2020},
institution = {Jiangnan University, China; University of Alberta, Canada; Zhejiang University, China},
abstract = {In this paper, an online estimator for faulty sensor signal is proposed for industrial processes described by nonlinear state-space models. The potential sensor fault is modeled as an unknown additive Gaussian signal, whose distribution is estimated together with the probability density function (PDF) of the state by using the variational Bayesian inference. To solve the problem that transition dynamics of faults are unavailable, a heuristic model with probabilistic features is discussed together with other commonly-used descriptions. For the computation issue caused by nonlinearities, a set of weighted particles is employed to estimate the PDF of state empirically, while the counterpart of the faulty signal is still calculated analytically. The effectiveness of the proposed algorithm is verified by a robot localization example and an experiment conducted on a flexible rotary joint. It shows that the proposed algorithm yields improvements over the existing algorithms, including the Bayesian estimator and the modified multiple-model-based method, and can satisfactorily estimate the magnitude of fault as well as its location in an online manner. },
issn = {0278-0046},
keywords = {Sensor Fault, Bayesian estimation, Variational inference, Particle approximation, Nonlinear systems},
language = {English},
publisher = {IEEE}
}

In this paper, an online estimator for faulty sensor signal is proposed for industrial processes described by nonlinear state-space models. The potential sensor fault is modeled as an unknown additive Gaussian signal, whose distribution is estimated together with the probability density function (PDF) of the state by using the variational Bayesian inference. To solve the problem that transition dynamics of faults are unavailable, a heuristic model with probabilistic features is discussed together with other commonly-used descriptions. For the computation issue caused by nonlinearities, a set of weighted particles is employed to estimate the PDF of state empirically, while the counterpart of the faulty signal is still calculated analytically. The effectiveness of the proposed algorithm is verified by a robot localization example and an experiment conducted on a flexible rotary joint. It shows that the proposed algorithm yields improvements over the existing algorithms, including the Bayesian estimator and the modified multiple-model-based method, and can satisfactorily estimate the magnitude of fault as well as its location in an online manner.

@article{mehedi_2020,
title = {Surgical robotic arm control for tissue ablation},
author = {Mehedi, I.M.; Rao, K.P.},
journal = {Journal of Robotic Surgery},
year = {2020},
institution = {King Abdulaziz University, Saudi Arabia},
abstract = {In the technology driven era, robot assisted surgery is gradually emerging as a revolutionized surgical procedure over traditional laparoscopic method. Despite the concerns about robotic surgery for minimally invasive surgical procedures, robotized surgical arms have been used in many hospitals. Certain surgical procedures require removal of a segment of an organ or body part like excision biopsy, linear thin layer of soft tissue, triangular mass, and tangential excision in burn management, where shaving-off at an angle of the tissue layer to be removed. For such minimally invasive procedures, we have designed a surgical arm governed by a rotary flexible joint. The surgical arm has a medical grade scalpel in its one end and the other end is connected to a D.C. servo motor. The motion of the surgical arm is controlled by the newly designed non-integer order controller. We have experimentally demonstrated the functioning of the surgical arm by ablating the tissue in-vitro. Our surgical robotic arm is cost effective, high precision and free from potential human errors. },
keywords = {Tissue ablation, Scalpel, Surgical robotic arm, Non-integer order controller, Flexible rotary joint},
language = {English}
}

In the technology driven era, robot assisted surgery is gradually emerging as a revolutionized surgical procedure over traditional laparoscopic method. Despite the concerns about robotic surgery for minimally invasive surgical procedures, robotized surgical arms have been used in many hospitals. Certain surgical procedures require removal of a segment of an organ or body part like excision biopsy, linear thin layer of soft tissue, triangular mass, and tangential excision in burn management, where shaving-off at an angle of the tissue layer to be removed. For such minimally invasive procedures, we have designed a surgical arm governed by a rotary flexible joint. The surgical arm has a medical grade scalpel in its one end and the other end is connected to a D.C. servo motor. The motion of the surgical arm is controlled by the newly designed non-integer order controller. We have experimentally demonstrated the functioning of the surgical arm by ablating the tissue in-vitro. Our surgical robotic arm is cost effective, high precision and free from potential human errors.

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

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

@conference{bluman_2019,
title = {Implementing a Full-state Feedback Laboratory Exercise in an Introductory Undergraduate Control Systems Engineering Course},
author = {Bluman, J.E.; Leger,A.St.; Korpela, C.M.},
booktitle = {2019 ASEE Annual Conference & Exposition},
year = {2019},
institution = {U.S. Military Academy, USA},
abstract = {Many mechanical engineering undergraduate students find the study of control systems engineering to be one of the more challenging subjects that they encounter. These challenges include working in the Laplace and frequency domains, learning new analysis techniques, as well as the breadth of topics that are typically covered in an introductory control systems undergraduate class. The challenges faced by instructors consist of deciding which material to include, balancing the depth and breadth of understanding various topics, selecting the best learning activities for each technique, and providing meaningful hands on experimentation in a predominately theoretical course. Fortunately, control systems engineering is amenable to instruction through laboratory exercises, where students can try different control techniques and observe their effectiveness nearly in real-time. Some effort is required to adequately link theory to experimentation in a theoretical introductory course. In this paper, we describe the implementation of a new full-state feedback laboratory exercise which was designed to illustrate the efficacy of full state control of a fourth order system. The general process of modeling, simulating the system, controller development, then deployment and evaluation in the lab is a common pedagogical process in control systems engineering education. The importance of visualization, in the context of using information technology, is discussed in Bencomo (2003). The laboratory exercise in view utilizes the same aforementioned process with an emphasis on visualizing system performance in state feedback control. The students first complete a pre-lab exercise which covers the modeling, control design, and simulation. Then they utilize commercially available software-hardware package that allows them to deploy their design and observe its real world performance. Specifically, the prelab begins by requiring them through modeling the dynamics of the electro-mechanical system. Furthermore the students then design the controller gains in a full state feedback in order to achieve a desired transient response. They then model the system in SIMULINK prior to coming to the lab, and analyze the effectiveness of their control design. The pre-lab assignments are submitted by the students, graded by the instructor, and then returned in the laboratory. In the laboratory, the students walk through a series of exercises beginning with the open loop response and ending with full state feedback in a closed loop sense. The intermediate steps allow the students to observe the improvements in the response of the system. The students are also introduced to signal processing requirements, for example the need to filter a differentiated signal. The novelty in this exercise lies in the procedural implementation of state feedback (no feedback, partial state feedback(s), and full state feedback with estimation) and evaluation of performance. Specifically, through visual observation of system performance and quantification of system performance through data acquisition and analysis. The full paper will provide the details of the laboratory including implementation instructions and lessons learned through conducting this laboratory exercise with students. },
language = {English},
publisher = {ASEE}
}

Many mechanical engineering undergraduate students find the study of control systems engineering to be one of the more challenging subjects that they encounter. These challenges include working in the Laplace and frequency domains, learning new analysis techniques, as well as the breadth of topics that are typically covered in an introductory control systems undergraduate class. The challenges faced by instructors consist of deciding which material to include, balancing the depth and breadth of understanding various topics, selecting the best learning activities for each technique, and providing meaningful hands on experimentation in a predominately theoretical course. Fortunately, control systems engineering is amenable to instruction through laboratory exercises, where students can try different control techniques and observe their effectiveness nearly in real-time. Some effort is required to adequately link theory to experimentation in a theoretical introductory course. In this paper, we describe the implementation of a new full-state feedback laboratory exercise which was designed to illustrate the efficacy of full state control of a fourth order system. The general process of modeling, simulating the system, controller development, then deployment and evaluation in the lab is a common pedagogical process in control systems engineering education. The importance of visualization, in the context of using information technology, is discussed in Bencomo (2003). The laboratory exercise in view utilizes the same aforementioned process with an emphasis on visualizing system performance in state feedback control. The students first complete a pre-lab exercise which covers the modeling, control design, and simulation. Then they utilize commercially available software-hardware package that allows them to deploy their design and observe its real world performance. Specifically, the prelab begins by requiring them through modeling the dynamics of the electro-mechanical system. Furthermore the students then design the controller gains in a full state feedback in order to achieve a desired transient response. They then model the system in SIMULINK prior to coming to the lab, and analyze the effectiveness of their control design. The pre-lab assignments are submitted by the students, graded by the instructor, and then returned in the laboratory. In the laboratory, the students walk through a series of exercises beginning with the open loop response and ending with full state feedback in a closed loop sense. The intermediate steps allow the students to observe the improvements in the response of the system. The students are also introduced to signal processing requirements, for example the need to filter a differentiated signal. The novelty in this exercise lies in the procedural implementation of state feedback (no feedback, partial state feedback(s), and full state feedback with estimation) and evaluation of performance. Specifically, through visual observation of system performance and quantification of system performance through data acquisition and analysis. The full paper will provide the details of the laboratory including implementation instructions and lessons learned through conducting this laboratory exercise with students.

@conference{sendrescu_2019,
title = {Iterative Learning Control for a Rotary Flexible Joint Experiment},
author = {Sendrescu, D.; Bujgoi, G.},
booktitle = {2019 20th International Carpathian Control Conference (ICCC)},
year = {2019},
institution = {University of Craiova, Romania; SC ALTUR S.A., Romania},
abstract = {This paper deals with the Iterative Learning Control (ILC) of a Flexible Joint Experiment. The paper presents a short overview of the field of Iterative Learning Control and some basic ILC strategies (P – type and D – type) are highlighted. The design of ILC for linear systems is briefly presented. The ILC is implemented on a Flexible Joint experiment, working in repetitive manner, where the control goal is the trajectory tracking. Even the Flexible Joint is a nonlinear system, in order to tune the controller parameters a linear model is derived. The controller performances are evaluated using a real plant experiment. The main experimental results are presented and the performance of the control system is analyzed. },
keywords = {Iterative Learning Control, robotic arm, flexible joint},
language = {English},
publisher = {IEEE},
isbn = {978-1-7281-0703-5}
}

This paper deals with the Iterative Learning Control (ILC) of a Flexible Joint Experiment. The paper presents a short overview of the field of Iterative Learning Control and some basic ILC strategies (P – type and D – type) are highlighted. The design of ILC for linear systems is briefly presented. The ILC is implemented on a Flexible Joint experiment, working in repetitive manner, where the control goal is the trajectory tracking. Even the Flexible Joint is a nonlinear system, in order to tune the controller parameters a linear model is derived. The controller performances are evaluated using a real plant experiment. The main experimental results are presented and the performance of the control system is analyzed.

@article{ettefagh_2019,
title = {Position Control of a Flexible Joint via Explicit Model Predictive Control: An Experimental Implementation},
author = {Ettefagh, M.H.; Naraghi, M.; Towhidkhah, F.},
journal = {Emerging Science Journal},
year = {2019},
volume = {3},
number = {3},
institution = {Amirkabir University of Technology, Iran},
abstract = {This paper experimentally controls a flexible joint via explicit model predictive control (Explicit MPC) method. The scheme divides the state space into different partitions, then solves the associated multi parametric optimization in off-line computations. The result stores in a look-up table to be used in on-line algorithm. First, the state space equations of the flexible joint are derived and linearized around the working point. Then, in order to meet the plant’s specifications, desired performance and the limitation of processor/memory, the constraints, weights, sampling time and prediction horizon are determined for the system. Finally, the algorithm is applied on the experimental plant. Numerous simulations, the result of the experiment and comparison with other methods confirmed that the method was able to control the vibrations of the constrained flexible joint. },
keywords = {Flexible Joint; Explicit Model Predictive Control; Multi-Parametric Optimization; Discrete Linear Time Invariant System},
language = {English},
publisher = {ESJ Italy},
pages = {146-156}
}

This paper experimentally controls a flexible joint via explicit model predictive control (Explicit MPC) method. The scheme divides the state space into different partitions, then solves the associated multi parametric optimization in off-line computations. The result stores in a look-up table to be used in on-line algorithm. First, the state space equations of the flexible joint are derived and linearized around the working point. Then, in order to meet the plant’s specifications, desired performance and the limitation of processor/memory, the constraints, weights, sampling time and prediction horizon are determined for the system. Finally, the algorithm is applied on the experimental plant. Numerous simulations, the result of the experiment and comparison with other methods confirmed that the method was able to control the vibrations of the constrained flexible joint.

@article{zhao_2019,
title = {Probabilistic Monitoring of Correlated Sensors for Nonlinear Processes in State-Space},
author = {Zhao, S.; Shmaliy, Y.S.; Ahn, C.K.; Zhao, C.},
journal = {IEEE Transactions on Industrial Electronics},
year = {2019},
institution = {Jiangnan University, China; Universidad de Guanajuato, Mexico; Korea University, Korea; Zhejiang University, China},
abstract = {To optimize control and/or state estimation of industrial processes, information about measurement quality provided by sensors is required. In this paper, a probabilistic scheme is proposed in discrete-time nonlinear state-space with the purpose of sensor monitoring. A quantitative index representing the measurement quality, as well as satisfied state estimates, is obtained by estimating the probability density functions (PDFs) of the states and the measurement noise covariance considered as a random variable using the variational Bayesian approach. To solve the intractable integrals of nonlinear PDFs in real time, a set of weighted particles is generated to overlap an empirical density of state, while the PDF of the measurement noise is still derived analytically. An example of localization and an experiment with a rotary flexible joint are supplied to demonstrate that the proposed algorithm significantly improves the applicability of existing methods and can monitor correlated sensors satisfactorily. },
issn = {0278-0046 },
keywords = {Sensor monitoring, variational Bayesian inference, particle approximation, nonlinear process, state estimation},
language = {English},
publisher = {IEEE}
}

To optimize control and/or state estimation of industrial processes, information about measurement quality provided by sensors is required. In this paper, a probabilistic scheme is proposed in discrete-time nonlinear state-space with the purpose of sensor monitoring. A quantitative index representing the measurement quality, as well as satisfied state estimates, is obtained by estimating the probability density functions (PDFs) of the states and the measurement noise covariance considered as a random variable using the variational Bayesian approach. To solve the intractable integrals of nonlinear PDFs in real time, a set of weighted particles is generated to overlap an empirical density of state, while the PDF of the measurement noise is still derived analytically. An example of localization and an experiment with a rotary flexible joint are supplied to demonstrate that the proposed algorithm significantly improves the applicability of existing methods and can monitor correlated sensors satisfactorily.

@article{xin_2019,
title = {Robust Experimental Study of Data-driven Optimal Control for an Underactuated Rotary Flexible Joint},
author = {Xin, Y.; Qin, Z.-C.; Sun, J.-Q.},
journal = {International Journal of Control, Automation and Systems},
year = {2019},
institution = {Tianjin University of Technology, China; Shandong University of Technology, China; University of California, USA},
abstract = {As an important component of industrial robot, the motion control of rotary flexible joint (RFJ) system is of great significance, especially when the system has unmodeled dynamics or is seriously disturbed. This paper presents an experimental robustness study on a kind data-driven optimal control approach based on an underactuated rotary flexible joint system. The data-driven approach combines the off-policy optimal control algorithm and the popular integral reinforcement learning technique. Through literature review, we find that the key step of the control design lies in that it learns the optimal value function and control policy simultaneously from the input and output (I/O) data. However, the I/O data are often disturbed by the system uncertainty or environmental noise, and then it will indirectly affect the optimal control performance. To investigate the robustness of the data-driven optimal control approach, we artificially set different experimental scenarios and take numerous control experiments on a RFJ experimental setup. The experimental results show that the data-driven optimal control method is quite robust against the system uncertainties in terms of maintaining the stability and delivering satisfactory tracking performance, even when the uncertainty is not a small quantity. In addition, the disturbance originating from environmental noise has certain impact on the controlling of RFJ system, but as long as the noise power is not too large, the control algorithm can converge to a satisfactory result. Finally, we find that the probing signal up has strong influence to this control algorithm, which reminds us to be cautious when selecting the probing signal. },
issn = {1598-6446},
keywords = {External disturbance, model-free optimal control, reinforcement learning, robustness study, rotary flexible joint, system uncertainty},
language = {English},
publisher = {Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers}
}

As an important component of industrial robot, the motion control of rotary flexible joint (RFJ) system is of great significance, especially when the system has unmodeled dynamics or is seriously disturbed. This paper presents an experimental robustness study on a kind data-driven optimal control approach based on an underactuated rotary flexible joint system. The data-driven approach combines the off-policy optimal control algorithm and the popular integral reinforcement learning technique. Through literature review, we find that the key step of the control design lies in that it learns the optimal value function and control policy simultaneously from the input and output (I/O) data. However, the I/O data are often disturbed by the system uncertainty or environmental noise, and then it will indirectly affect the optimal control performance. To investigate the robustness of the data-driven optimal control approach, we artificially set different experimental scenarios and take numerous control experiments on a RFJ experimental setup. The experimental results show that the data-driven optimal control method is quite robust against the system uncertainties in terms of maintaining the stability and delivering satisfactory tracking performance, even when the uncertainty is not a small quantity. In addition, the disturbance originating from environmental noise has certain impact on the controlling of RFJ system, but as long as the noise power is not too large, the control algorithm can converge to a satisfactory result. Finally, we find that the probing signal up has strong influence to this control algorithm, which reminds us to be cautious when selecting the probing signal.

@article{chun_2018,
title = {Simultaneous identification of model structure and the associated parameters for linear systems based on particle swarm optimization},
author = {Chun, S.; Kim, T.-H.},
journal = {Complexity},
year = {2018},
institution = {Chung-Ang University, South Korea},
abstract = {In this study, a novel easy-to-use meta-heuristic method for simultaneous identification of model structure and the associated parameters for linear systems is developed. This is achieved via a constrained multi-dimensional particle swarm optimization (PSO) mechanism developed by hybridizing two main methodologies: one for negating the limit for fixing the particles dimensions within the PSO process and another for enhancing the exploration ability of the particles by adopting a cyclic neighborhood topology of the swarm. This optimizer consecutively searches the dimensional optimum of particles and then the positional optimum in the search space, whose dimension is specified by the explored optimal dimension. The dimensional optimum provides the optimal model structure, while the positional optimum provides the optimal model parameters. Typical numerical examples are considered for evaluation purposes, which clearly demonstrate that the proposed PSO scheme provides novel and powerful impetus with remarkable reliability toward simultaneous identification of model structure and unknown model parameters. Furthermore, identification experiments are conducted on a magnetic levitation system and a robotic manipulator with joint flexibility to demonstrate the effectiveness of the proposed strategy in practical applications. },
keywords = {System identification, model structure estimation, model parameter estimation, particle swarm optimization},
language = {English},
publisher = {Hindawi Publishing Corp.}
}

In this study, a novel easy-to-use meta-heuristic method for simultaneous identification of model structure and the associated parameters for linear systems is developed. This is achieved via a constrained multi-dimensional particle swarm optimization (PSO) mechanism developed by hybridizing two main methodologies: one for negating the limit for fixing the particles dimensions within the PSO process and another for enhancing the exploration ability of the particles by adopting a cyclic neighborhood topology of the swarm. This optimizer consecutively searches the dimensional optimum of particles and then the positional optimum in the search space, whose dimension is specified by the explored optimal dimension. The dimensional optimum provides the optimal model structure, while the positional optimum provides the optimal model parameters. Typical numerical examples are considered for evaluation purposes, which clearly demonstrate that the proposed PSO scheme provides novel and powerful impetus with remarkable reliability toward simultaneous identification of model structure and unknown model parameters. Furthermore, identification experiments are conducted on a magnetic levitation system and a robotic manipulator with joint flexibility to demonstrate the effectiveness of the proposed strategy in practical applications.

@article{guinaldo_2017,
title = {Event-based control for networked systems: From centralized to distributed approaches},
author = {Guinaldo, M.; Sanchez, J.; Dormido, S.},
journal = {Revista Iberoamericana de Automàtica e Informàtica Industrial},
year = {2017},
volume = {14},
number = {1},
institution = {Departamento de Informàtica y Automàtica, UNED, Espana},
abstract = {Networked control systems (NCSs) are spatially distributed systems in which sensors, actuators and controllers exchange information through a communication channel or network. The reduction in the amount of transmitted information has a relevant impact over the system's performance. In this regard, non-conventional communication rules, such as the event-based control, have been demonstrated to be effective. In this paper, some of these strategies are reviewed. We first focus on centralized NCSs, and then the distributed control for large-scale systems is studied. Finally, some of the results are applied to the formation control problem and implemented over an experimental setup. },
keywords = {Networked control; event-based control; distributed control; large-scale system; multi-agent system; formation control; mobile robot},
publisher = {Elsevier Ltd.},
pages = {16-30}
}

Networked control systems (NCSs) are spatially distributed systems in which sensors, actuators and controllers exchange information through a communication channel or network. The reduction in the amount of transmitted information has a relevant impact over the system's performance. In this regard, non-conventional communication rules, such as the event-based control, have been demonstrated to be effective. In this paper, some of these strategies are reviewed. We first focus on centralized NCSs, and then the distributed control for large-scale systems is studied. Finally, some of the results are applied to the formation control problem and implemented over an experimental setup.

@conference{bilal_2017,
title = {Experimental validation of fuzzy PID control of flexible joint system in presence of uncertainties},
author = {Bilal, H.; Yao, W.; Guo, Y.; Wu, Y.; Guo, J.},
booktitle = {2017 36th Chinese Control Conference (CCC)},
year = {2017},
institution = { Nanjing University of Science and Technology, China},
abstract = {In this paper, a robust fuzzy-tuned PID controller is proposed for the trajectory tracking and vibration control of a flexible joint manipulator system (FJMS) with parametric uncertainties. Flexible joint manipulators are widely used in industry due to their flexibility, light in weight and fast response, low cost, and low energy consumption. The dynamic modeling via Euler-Lagrange equation for a single link flexible joint manipulator system (FJMS) is presented first. By analyzing the characteristics of the high order linear system, the Fuzzy-Tuned PID control strategy is utilized. The parameters of classical PID controller are updated by the intelligent method of fuzzy logic. With the adaptivity to the parametric uncertainties from the system stiffness and moment of inertia, the contrived approach provides more efficient results compared to existing techniques in terms of vibration suppressions, time response, and overshoot. Finally, the effectiveness of the controller is corroborated through multiple experiments on the QUANSER's flexible joint manipulator system (FJMS). },
keywords = {Fuzzy Tuned PID Control, Vibration Suppressions, Trajectory Tracking, Flexible Joint Manipulator},
language = {English},
publisher = {IEEE}
}

In this paper, a robust fuzzy-tuned PID controller is proposed for the trajectory tracking and vibration control of a flexible joint manipulator system (FJMS) with parametric uncertainties. Flexible joint manipulators are widely used in industry due to their flexibility, light in weight and fast response, low cost, and low energy consumption. The dynamic modeling via Euler-Lagrange equation for a single link flexible joint manipulator system (FJMS) is presented first. By analyzing the characteristics of the high order linear system, the Fuzzy-Tuned PID control strategy is utilized. The parameters of classical PID controller are updated by the intelligent method of fuzzy logic. With the adaptivity to the parametric uncertainties from the system stiffness and moment of inertia, the contrived approach provides more efficient results compared to existing techniques in terms of vibration suppressions, time response, and overshoot. Finally, the effectiveness of the controller is corroborated through multiple experiments on the QUANSER's flexible joint manipulator system (FJMS).

@article{al-saggaf_2107,
title = {Rotary flexible joint control by fractional order controllers},
author = {Al-Saggaf, U.M.; Mehedi, I.M.; Mansouri, R.; Bettayeb, M.},
journal = {International Journal of Control, Automation and Systems},
year = {2017},
institution = {King Abdulaziz University, Saudi Arabia; Mouloud Mammeri University, Algeria; University of Sharjah, United Arab Emirates},
abstract = {In this paper, a fractional order control law is proposed and implemented for the evaluation of trajectory tracking performance of a rotary flexible-joint system. A state feedback based fractional integral control scheme is used in this proposed method. In this scheme, state feedback is responsible for stabilizing the system. The compensator, in series with the fractional integrator leads to obtain a similar closed-loop transient response like Bode’s ideal transfer function. The effectiveness of the proposed controller in tracking and being robust against parameter uncertainties is demonstrated through simulation. In addition, to show the usefulness of the proposed control scheme, the fractional controller is compared to an integer state feedback control by simulation and through experimentation on the Quanser’s rotary flexible-joint system. },
issn = {1598-6446},
keywords = {Bode’s ideal transfer function, flexible-joint system, fractional integral control, fractional order controller, state feedback },
language = {English},
publisher = {Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers}
}

In this paper, a fractional order control law is proposed and implemented for the evaluation of trajectory tracking performance of a rotary flexible-joint system. A state feedback based fractional integral control scheme is used in this proposed method. In this scheme, state feedback is responsible for stabilizing the system. The compensator, in series with the fractional integrator leads to obtain a similar closed-loop transient response like Bode’s ideal transfer function. The effectiveness of the proposed controller in tracking and being robust against parameter uncertainties is demonstrated through simulation. In addition, to show the usefulness of the proposed control scheme, the fractional controller is compared to an integer state feedback control by simulation and through experimentation on the Quanser’s rotary flexible-joint system.

@article{qin_2016,
title = {An Experimental Study of Robustness of Multi-objective Optimal Sliding Mode Control},
author = {Qin, Z.-C.; Xiong, F.-R.; Sun, J.-Q.},
journal = {Journal of Vibration and Acoustics},
year = {2016},
abstract = {This paper presents an experimental study of robustness of multi-objective optimal sliding mode control, which is designed in a previous study. Inertial and stiffness uncertainties are introduced to a two-degree-of-freedom under-actuated rotary flexible joint system. A randomly selected design from the Pareto set of multi-objective optimal sliding mode controls is used in the experiments. Three indices are introduced to evaluate the performance variation of the tracking control in the presence of uncertainties. We have found that the multi-objective optimal sliding mode control is quite robust against the inertial and stiffness uncertainties in terms of maintaining the stability and delivering satisfactory tracking performance as compared to the control of the nominal system, even when the uncertainty is not a small quantity. Furthermore, we have studied the effect of upper bounds of the model estimation error on the stability of the closed-loop system. },
keywords = {Sliding mode control, Robustness, Uncertainty, Stability, Stiffness, Tracking control, Design, Closed loop systems, Errors},
language = {English},
publisher = {ASME}
}

This paper presents an experimental study of robustness of multi-objective optimal sliding mode control, which is designed in a previous study. Inertial and stiffness uncertainties are introduced to a two-degree-of-freedom under-actuated rotary flexible joint system. A randomly selected design from the Pareto set of multi-objective optimal sliding mode controls is used in the experiments. Three indices are introduced to evaluate the performance variation of the tracking control in the presence of uncertainties. We have found that the multi-objective optimal sliding mode control is quite robust against the inertial and stiffness uncertainties in terms of maintaining the stability and delivering satisfactory tracking performance as compared to the control of the nominal system, even when the uncertainty is not a small quantity. Furthermore, we have studied the effect of upper bounds of the model estimation error on the stability of the closed-loop system.

@conference{khan_2016,
title = {Beyond Linear Control Approaches – Sliding Mode Control of Flexible Robotic Manipulator},
author = {Khan O.; Rehman, A.U.R.; Pervaiz, M.},
booktitle = {2016 International Conference on Frontiers of Information Technology (FIT)},
year = {2016},
institution = {COMSATS Institute of Information Technology, Pakistan},
abstract = {Flexibility in robotic manipulators offers various benefits in terms of operational speed, power consumption, maneuverability, and weight. However, these advantages lead to complex controller design. This paper presents two laws, nonlinear sliding mode control (SMC) and linear quadratic regulator (LQR) for addressing the control problem of flexible joint manipulator. The aim is to accurately track the position of link with considerable minimum oscillations, encountered due to flexibility of joint. The novelty of the derived Lagrangian-based dynamic model lies in consideration of both critical effects, gravity and viscous damping. Feedback linearization is used to linearize the system. The designed control laws are then subjected to several test inputs for comparing and characterizing their tracking performance. Comparative results reveal that SMC outperforms than LQR in trajectory tracking. Results of this research can be used in several flexible robotic manipulator (FRM) applications including medical, space and industrial automation. },
keywords = {feedback linearization, robust control, robotic manipulator, linear control, robustness, flexible joint},
language = {English}
}

Flexibility in robotic manipulators offers various benefits in terms of operational speed, power consumption, maneuverability, and weight. However, these advantages lead to complex controller design. This paper presents two laws, nonlinear sliding mode control (SMC) and linear quadratic regulator (LQR) for addressing the control problem of flexible joint manipulator. The aim is to accurately track the position of link with considerable minimum oscillations, encountered due to flexibility of joint. The novelty of the derived Lagrangian-based dynamic model lies in consideration of both critical effects, gravity and viscous damping. Feedback linearization is used to linearize the system. The designed control laws are then subjected to several test inputs for comparing and characterizing their tracking performance. Comparative results reveal that SMC outperforms than LQR in trajectory tracking. Results of this research can be used in several flexible robotic manipulator (FRM) applications including medical, space and industrial automation.

@conference{markus_2016,
title = {Experimental validation on flatness based control of flexible robot arm},
author = {Markus, E.D.},
booktitle = {Pattern Recognition Association of South Africa and Robotics and Mechatronics International Conference (PRASA-RobMech) 2016},
year = {2016},
institution = {Central University of Technology, South Africa},
abstract = {This paper discusses the practical implementation of a flatness based control for a flexible joint robot arm. Using differential flatness theory, reference trajectories are generated for a flexible joint robot and then a tracking controller is implemented. The vibrations experienced by the robot arm are sufficiently damped and nonminimum phase behaviour is eliminated. The control shows fast transcient response as desired for flexible robots. Experimental results proves the effectiveness of the flatness based control approach. },
keywords = {Flexible robot arm, Differential flatness, nonlinear control, trajectory tracking},
language = {English},
publisher = {IEEE},
isbn = {978-1-5090-3336-2}
}

This paper discusses the practical implementation of a flatness based control for a flexible joint robot arm. Using differential flatness theory, reference trajectories are generated for a flexible joint robot and then a tracking controller is implemented. The vibrations experienced by the robot arm are sufficiently damped and nonminimum phase behaviour is eliminated. The control shows fast transcient response as desired for flexible robots. Experimental results proves the effectiveness of the flatness based control approach.

@article{aziz_2016,
title = {Going Beyond Rigid Manipulators _ A Review of Control of Flexible Robotic Arms},
author = {Aziz, H.M.W.; Maqsood, I.; Wajahat, M.; Afzal. A.A.; Iqbal, J.},
year = {2016},
institution = {FAST National University of Computer and Emerging Sciences, Pakistan},
abstract = {Robots are now an integral part of automation sector, thus indicating the importance of the associated control strategies. In contrast with conventional rigid manipulators, flexible arms offer several benefits in terms of light weight and power efficient structure, safe operation due to reduced inertia, low manufacturing cost and faster movements. The present paper systematically reviews the key linear as well as nonlinear techniques to control flexible manipulators. Flexibility in link as well as in joint is discussed highlighting the control challenges. It is anticipated that this in-depth study will be potentially beneficial for researchers, control engineers and industrial interns. },
keywords = {Robotics; Flexible Robotic Arm; Control Techniques},
language = {English}
}

Robots are now an integral part of automation sector, thus indicating the importance of the associated control strategies. In contrast with conventional rigid manipulators, flexible arms offer several benefits in terms of light weight and power efficient structure, safe operation due to reduced inertia, low manufacturing cost and faster movements. The present paper systematically reviews the key linear as well as nonlinear techniques to control flexible manipulators. Flexibility in link as well as in joint is discussed highlighting the control challenges. It is anticipated that this in-depth study will be potentially beneficial for researchers, control engineers and industrial interns.

@conference{rseatam_2016,
title = {Hierarchical sliding mode control applied to a single-link flexible joint robot manipulator},
author = {Rsetam, K.; Cao, Z.; Man, Z.},
booktitle = {2016 International Conference on Advanced Mechatronic Systems (ICAMechS)},
year = {2016},
institution = {Swinburne University of Technology, Melbourne, Australia},
abstract = {Trajectory tracking and vibration suppression are essential objectives in a flexible joint manipulator control. The flexible joint manipulator is an under-actuated system, in which the number of control actions is less than the degree of freedom to be controlled. It is very challenging to control the under-actuated nonlinear system with two degree of freedom. This paper presents a hierarchical sliding mode control (HSMC) for a rotary flexible joint manipulator (RFJM). Firstly, the rotary flexible joint manipulator is modeled by two subsystems. Secondly, the sliding surfaces for both subsystems are constructed. Finally, the control action is designed based on the Lyapunov function. Computer simulation results demonstrate the effectiveness of the proposed control. The comparative study shows the proposed method has superior performance than the conventional sliding mode control by achieving the controlled objectives such as a satisfactory tracking performance and an acceptable vibration reduction for the single link flexible joint robot manipulator. },
keywords = {flexible-joint robot; hierachical sliding mode controller; under-actuated systems; Lyapunov stability theory, copuling},
language = {English},
publisher = {IEEE}
}

Trajectory tracking and vibration suppression are essential objectives in a flexible joint manipulator control. The flexible joint manipulator is an under-actuated system, in which the number of control actions is less than the degree of freedom to be controlled. It is very challenging to control the under-actuated nonlinear system with two degree of freedom. This paper presents a hierarchical sliding mode control (HSMC) for a rotary flexible joint manipulator (RFJM). Firstly, the rotary flexible joint manipulator is modeled by two subsystems. Secondly, the sliding surfaces for both subsystems are constructed. Finally, the control action is designed based on the Lyapunov function. Computer simulation results demonstrate the effectiveness of the proposed control. The comparative study shows the proposed method has superior performance than the conventional sliding mode control by achieving the controlled objectives such as a satisfactory tracking performance and an acceptable vibration reduction for the single link flexible joint robot manipulator.

@article{ghazali_2016,
title = {Single input fuzzy logic controller for flexible joint manipulator},
author = {Ghazali, M.R.; Ibrahim, Z.; Suid, M.H.; Saealal, M.S.; Tumari, M.Z.M.},
journal = {International Journal of Innovative Computing, Information and Control},
year = {2016},
volume = {12},
number = {1},
abstract = {oint elasticity in the dynamics of robots manipulator makes the conventional model-based control strategies complex and difficult to synthesize. This paper presents investigations into the development of single input fuzzy logic controller (SIFLC) for tip angular position tracking and deflection angle reduction of a flexible joint manipulator system. A Quanser flexible joint manipulator system is considered and the dynamic model of the system is derived using the Euler-Lagrange formulation. The proposed method, known as the SIFLC, reduces the conventional two-input FLC (CFLC) to a single input single output (SISO) controller. Two parallel SIFLC are developed for both tip angular position and deflection angle control. The proposed control scheme is also compared with existing results by Ahmad et al., which are hybrid proportional-derivative (PD) with low-pass filter (LPF) and PD with non-collocated fuzzy logic control schemes. The performances of the control schemes are assessed in terms of tip angular tracking capability, level of deflection angle reduction and time response specifications. Finally, a comparative assessment of the control techniques is presented and discussed. },
issn = {1349-4198},
keywords = {Flexible joint, Vibration control, Intelligent controller, Classical controller},
language = {English},
publisher = {ICIC International},
pages = {181-191}
}

oint elasticity in the dynamics of robots manipulator makes the conventional model-based control strategies complex and difficult to synthesize. This paper presents investigations into the development of single input fuzzy logic controller (SIFLC) for tip angular position tracking and deflection angle reduction of a flexible joint manipulator system. A Quanser flexible joint manipulator system is considered and the dynamic model of the system is derived using the Euler-Lagrange formulation. The proposed method, known as the SIFLC, reduces the conventional two-input FLC (CFLC) to a single input single output (SISO) controller. Two parallel SIFLC are developed for both tip angular position and deflection angle control. The proposed control scheme is also compared with existing results by Ahmad et al., which are hybrid proportional-derivative (PD) with low-pass filter (LPF) and PD with non-collocated fuzzy logic control schemes. The performances of the control schemes are assessed in terms of tip angular tracking capability, level of deflection angle reduction and time response specifications. Finally, a comparative assessment of the control techniques is presented and discussed.

@inproceedings{jalani_2016,
title = {The implementation of Takagi-Sugeno fuzzy for a rotary flexible joint robotic arm},
author = {Jalani, J.; Jayaraman, S.},
booktitle = {AIP Conference Proceedings 2016},
year = {2016},
institution = {University Tun Hussein Onn Malaysia},
abstract = {The research establishes a Takagi-Sugeno Fuzzy controller to control a desired tip angle position of a rotary flexible joint robotic arm. The TSF is also employed to dampen the vibration that produced when a rotary flexible joint robotic arm reaching to a desired tip angle position. In order to assess the controller performance, the proposed TSF is compared with the Linear Quadratic Regulator (LQR) controller via simulation and experiment. In particular, there are two different angles affect the system performance that need to be controlled namely the servo angle, and the arm deflection. The results showed that the TSF is satisfactorily controlled both the servo angle, and the arm deflection. In addition, the TSF performed better than LQR controller in simulation and experiment },
language = {English},
publisher = {American Institute of Physics}
}

The research establishes a Takagi-Sugeno Fuzzy controller to control a desired tip angle position of a rotary flexible joint robotic arm. The TSF is also employed to dampen the vibration that produced when a rotary flexible joint robotic arm reaching to a desired tip angle position. In order to assess the controller performance, the proposed TSF is compared with the Linear Quadratic Regulator (LQR) controller via simulation and experiment. In particular, there are two different angles affect the system performance that need to be controlled namely the servo angle, and the arm deflection. The results showed that the TSF is satisfactorily controlled both the
servo angle, and the arm deflection. In addition, the TSF performed better than LQR controller in simulation and experiment

@article{suryawanshi_2015,
title = {A boundary layer sliding mode control design for chatter reduction using uncertainty and disturbance estimator},
author = {Suryawanshi, Prasheel V.; Shendge, Pramod D.; Phadke, Shrivijay B.},
journal = {International Journal of Dynamics and Control},
year = {2015},
abstract = {This paper proposes a new boundary layer sliding mode control design for chatter reduction. The control scheme uses a discontinuous control outside the boundary layer and switches over to uncertainty and disturbance estimator (UDE) based control inside. The problem of large initial control underlying the method of UDE, is also addressed with a modified sliding surface. The overall stability of the system is proved and the results are verified on an illustrative example and application to flexible joint system. The results show that the proposed method exhibits much better control performance than the baseline SMC using ïsatÍ function, for reduced chattering. },
issn = {2195-2698},
keywords = {Sliding mode control, Uncertainty and disturbance estimator, Chatter, Flexible joint},
language = {English},
publisher = {Springer Berlin Heidelberg}
}

This paper proposes a new boundary layer sliding mode control design for chatter reduction. The control scheme uses a discontinuous control outside the boundary layer and switches over to uncertainty and disturbance estimator (UDE) based control inside. The problem of large initial control underlying the method of UDE, is also addressed with a modified sliding surface. The overall stability of the system is proved and the results are verified on an illustrative example and application to flexible joint system. The results show that the proposed method exhibits much better control performance than the baseline SMC using ïsatÍ function, for reduced chattering.

@article{beyhan_2015,
title = {Adaptive Fuzzy Terminal Sliding-Mode Observer with Experimental Applications},
author = {Beyhan, S.},
journal = {Int.J.Fuzzy Syst.},
year = {2015},
institution = {Pamukkale University, Turkey},
abstract = {In this paper, conventional gradient-descent-based adaptive fuzzy observer is improved by using the terminal sliding-mode theory for a class of nonlinear systems. The improvement is made in two ways: first, the switching term of the sliding-mode approach is added to the state of the observer. Second, the measurement error of the system is designed as the input of the observer instead of measured state. The stability of the observer and boundedness of the parameters are proved using Lyapunov approach. Contributions of the paper are summarized as follows: (i) the robustness and convergence properties of newly proposed observer are improved, (ii) the proposed adaptive fuzzy terminal sliding-mode observer, conventional adaptive fuzzy observer, adaptive neural-network observer, and Euler filtering approaches are compared in terms of their ability to estimate velocities of three real-time experimental systems reliably. The performance of the designed observers is discussed with root mean squared-error criterion where the proposed adaptive fuzzy terminal sliding-mode observer provided much accurate state estimation results than classical observers. },
issn = {1562-2479},
keywords = {Adaptive fuzzy observer, Terminal sliding-mode theory, Stability, Real-time mechanical systems},
language = {English},
publisher = {Springer-Verlag}
}

In this paper, conventional gradient-descent-based adaptive fuzzy observer is improved by using the terminal sliding-mode theory for a class of nonlinear systems. The improvement is made in two ways: first, the switching term of the sliding-mode approach is added to the state of the observer. Second, the measurement error of the system is designed as the input of the observer instead of measured state. The stability of the observer and boundedness of the parameters are proved using Lyapunov approach. Contributions of the paper are summarized as follows: (i) the robustness and convergence properties of newly proposed observer are improved, (ii) the proposed adaptive fuzzy terminal sliding-mode observer, conventional adaptive fuzzy observer, adaptive neural-network observer, and Euler filtering approaches are compared in terms of their ability to estimate velocities of three real-time experimental systems reliably. The performance of the designed observers is discussed with root mean squared-error criterion where the proposed adaptive fuzzy terminal sliding-mode observer provided much accurate state estimation results than classical observers.

@article{qin_2015,
title = {Multi-objective optimal design of sliding mode control with parallel simple cell mapping method},
author = {Zhi-Chang Qin, Fu-Rui Xiong, Qian Ding, Carlos Hernandez, Jesus Fernandez, Oliver Schutze, Jian-Qiao Sun},
journal = {Journal of Vibration and Control},
year = {2015},
abstract = {This paper presents a study of the multi-objective optimal design of a sliding mode control for an under-actuated nonlinear system with the parallel simple cell mapping method. The multi-objective optimal design of the sliding mode control involves six design parameters and five objective functions. The parallel simple cell mapping method finds the Pareto set and Pareto front efficiently. The parallel computing is done on a graphics processing unit. Numerical simulations and experiments are done on a rotary flexible arm system. The results show that the proposed multi-objective designs are quite effective. },
keywords = {Sliding mode control, simple cell mapping, multi-objective optimization, parallel computing, graphics processing unit (GPU)}
}

This paper presents a study of the multi-objective optimal design of a sliding mode control for an under-actuated nonlinear system with the parallel simple cell mapping method. The multi-objective optimal design of the sliding mode control involves six design parameters and five objective functions. The parallel simple cell mapping method finds the Pareto set and Pareto front efficiently. The parallel computing is done on a graphics processing unit. Numerical simulations and experiments are done on a rotary flexible arm system. The results show that the proposed multi-objective designs are quite effective.

@article{resceanu_2015,
title = {System Control In Fault And Normal Conditions Case Study – Quanser SRV-02},
author = {Resceanu, I.C.; Resceanu, C.F.},
journal = {ACTA Universitatis Cibiniensis},
year = {2015},
volume = {67},
number = {1},
institution = {Department of Mechatronics and Robotics, University of Craiova, Romania},
abstract = {A fault tolerant control method is proposed for Quanser SRV-02 System in order to maintain the required performance in the presence of sensor failures. The proposed approach integrates control law and a sensor fault tolerance schema. Theoretical analysis and simulation results have confirmed the effectiveness of the proposed method. },
issn = {1583-7149},
keywords = {Fault tolerant systems, Control systems},
language = {English}
}

A fault tolerant control method is proposed for Quanser SRV-02 System in order to maintain the required performance in the presence of sensor failures. The proposed approach integrates control law and a sensor fault tolerance schema. Theoretical analysis and simulation results have confirmed the effectiveness of the proposed method.

@article{kandroodi_2014,
title = {Control of Flexible Joint Manipulator via Variable Structure Rule-Based Fuzzy Control and Chaos Anti-Control with Experimental Validation},
author = {Mojtaba Rostami Kandroodi, Faezeh Farivar and Mahdi Aliyari Shoorehdel},
journal = {Intelligence Systems in Electrical Engineering},
year = {2014},
number = {4},
abstract = {This paper presents a variable structure rule-based fuzzy control for trajectory tracking and vibration control of a flexible joint manipul ator by using chaotic anti-contro l. Based on Lyapunov stability theory for variable structure control a nd fuzzy rules, the nonlinear controller and some generic sufficient conditions for global asymptotic control are attained. The fuzzy rules are directly constructed subject to a Lyapunov function obtaine d from variable structure surfaces such that the error dynamics of control problem satisfy stability in the Lyapunov sense. Also in this study, the anti-cont rol is applied to reduce the deflection angle of flexible join t system. To achieve this goal, the chaos dynamic must be created in the flexible joint system. So, the flexible joint system has been synchronized to chaotic gyroscope system. In this study, control and anti-control concepts are applied to achieve the high quality performance of flexible joint system. It is tried to design a controller which is capable to satisfy the control and anti- control aims. The performances of the proposed control are examined in terms of input tracking capability, level of vibration reduction and time res ponse specifications. Finally , the efficacy of the proposed method is validated through experiment ation on QUANSERÍs flexible-joint manipulator. },
keywords = {Anti-control; Chaos synchronization; Chaotic gyroscope; Flexible joint, Fuzzy control, Variable structure control},
language = {English}
}

This paper presents a variable structure rule-based fuzzy control for trajectory tracking and vibration control of a flexible joint manipul ator by using chaotic anti-contro l. Based on Lyapunov stability theory for variable structure control a nd fuzzy rules, the nonlinear controller and some generic sufficient conditions for global asymptotic control are attained. The fuzzy rules are directly constructed subject to a Lyapunov function obtaine d from variable structure surfaces such that the error dynamics of control problem satisfy stability in the Lyapunov sense. Also in this study, the anti-cont rol is applied to reduce the deflection angle of flexible join t system. To achieve this goal, the chaos dynamic must be created in the flexible joint system. So, the flexible joint system has been synchronized to chaotic gyroscope system. In this study, control and anti-control concepts are applied to achieve the high quality performance of flexible joint system. It is tried to design a controller which is capable to satisfy the control and anti- control aims. The performances of the proposed control are examined in terms of input tracking capability, level of vibration reduction and time res ponse specifications. Finally , the efficacy of the proposed method is validated through experiment ation on QUANSERÍs flexible-joint manipulator.

@article{zlotnik_2014,
title = {Saturated control of flexible-joint manipulators using a Hammerstein strictly positive real compensator},
author = {Caverly, R.J.; Zlotnik, D.E.; Forbes, J.R.},
journal = {Robotica},
year = {2014},
abstract = {In this paper the control of flexible-joint manipulators while explicitly avoiding actuator saturation is considered. The controllers investigated are composed of a bounded proportional control term and a Hammerstein strictly positive real angular rate control term. This control structure ensures that the total torque demanded of each actuator is bounded by a value that is less than the maximum torque that each actuator is able to provide, thereby disallowing actuator saturation. The proposed controllers are shown to render the closed-loop system asymptotically stable, even in the presence of modeling uncertainties. The performance of the controllers is demonstrated experimentally and in simulation. },
keywords = {Control of robotic systems; Actuator saturation; Flexible-joint manipulators; Gibbs parameter; Serial manipulator; SPR compensator},
publisher = {Cambridge University Press}
}

In this paper the control of flexible-joint manipulators while explicitly avoiding actuator saturation is considered. The controllers investigated are composed of a bounded proportional control term and a Hammerstein strictly positive real angular rate control term. This control structure ensures that the total torque demanded of each actuator is bounded by a value that is less than the maximum torque that each actuator is able to provide, thereby disallowing actuator saturation. The proposed controllers are shown to render the closed-loop system asymptotically stable, even in the presence of modeling uncertainties. The performance of the controllers is demonstrated experimentally and in simulation.

@article{caverly_2014,
title = {Saturated proportional derivative control of flexible-joint manipulators},
author = {Caverly, R.J.; Zlotnik, D.E.; bridgeman, L.J.; Forbes, J.R.},
journal = {Robotics and Computer-Integrated Manufacturing},
year = {2014},
volume = {130},
number = {6},
abstract = {In this paper, the control of flexible-joint robotic manipulators while avoiding actuator saturation is investigated. Several proportional derivative controllers are developed, all of which disallow actuator saturation by guaranteeing that the applied torque is less than a specified maximum value. In particular, a Gibbs parameterization of the joint angles is included in the control laws, which allows for an increased control torque as compared to an Euler angle parameterization. An equilibrium point of the closed-loop system is proven to be asymptotically stable using the Lyapunov stability analysis. Moreover, the proposed control laws do not require any knowledge of the manipulator?s mass, stiffness, or dissipation properties, and as such, are robust to modelling errors. The proposed controllers are tested on a single-link flexible-joint manipulator experimentally and on a two-link flexible-joint manipulator in simulation, and are compared to the performance of controllers found in the literature. },
keywords = {Saturation avoidance; Flexible-joint manipulator; Actuator saturation; Proportional-derivative control},
language = {English},
publisher = {Elsevier Ltd.},
pages = {658_666}
}

In this paper, the control of flexible-joint robotic manipulators while avoiding actuator saturation is investigated. Several proportional derivative controllers are developed, all of which disallow actuator saturation by guaranteeing that the applied torque is less than a specified maximum value. In particular, a Gibbs parameterization of the joint angles is included in the control laws, which allows for an increased control torque as compared to an Euler angle parameterization. An equilibrium point of the closed-loop system is proven to be asymptotically stable using the Lyapunov stability analysis. Moreover, the proposed control laws do not require any knowledge of the manipulator?s mass, stiffness, or dissipation properties, and as such, are robust to modelling errors. The proposed controllers are tested on a single-link flexible-joint manipulator experimentally and on a two-link flexible-joint manipulator in simulation, and are compared to the performance of controllers found in the literature.

@inproceedings{qin_2013,
title = {Experiments of Sliding Mode Control of Time-Delayed Dynamical Systems With Model Uncertainty},
author = {Zhi-Chang Qin, Shun Zhong and Jian-Qiao Sun},
booktitle = {ASME 2013 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference},
year = {2013},
abstract = {This paper presents simulation and experimental results of sliding mode control of nonlinear mechanical systems with time delay in the control loop. A flexible link oscillator made by Quanser is used as the target system. Geometric nonlinearity of the spring is included in the model, and the system is assumed to have parameter uncertainties. A sliding mode control with time delay is designed with the method of continuous time approximation. Both computer simulations and experiments show that the sliding mode control gives quite robust performance in the presence of model uncertainty. },
keywords = {Sliding mode control, Dynamic systems, Uncertainty},
isbn = {978-0-7918-5597-3}
}

This paper presents simulation and experimental results of sliding mode control of nonlinear mechanical systems with time delay in the control loop. A flexible link oscillator made by Quanser is used as the target system. Geometric nonlinearity of the spring is included in the model, and the system is assumed to have parameter uncertainties. A sliding mode control with time delay is designed with the method of continuous time approximation. Both computer simulations and experiments show that the sliding mode control gives quite robust performance in the presence of model uncertainty.

@conference{sandgani_2013,
title = {Lyapunov Rule-Based Fuzzy Control and Chaotic Anti-Control for Flexible Joint System and Analysis of Chaotic Signal Existence Effectiveness with Experimental Validation},
author = {Sandgani, M.R.; Shoorehdeli, M.A.},
booktitle = {2013 13th Iranian Conference on Fuzzy Systems (IFSC) },
year = {2013},
institution = {K. N. Toosi University of Technology, Iran},
abstract = {This study proposes a novel chaotic anti-control for flexible joint system. The proposed controller is composed of a Lyapunov rule-based fuzzy control and chaotic anti-control for target tracking of the flexible joint manipulator. Chaotic signal is used to study the effect of anti-control to reduce the deflection of flexible joint system and control signal energy. For this purposes the flexible joint has been synchronized with chaotic Lorenz system. In this study on of the Lorenz parameters is changed to analysis the effect of chaotic signals. The results of the proposed approach shows in terms of level of vibration reduction and energy consumption of control signal, we could find an optimum point based on value of Lorenz system parameter. Finally, the efficacy of the proposed method and results of existence of different nonlinearity behavior is validated through experiments on QUANSER’s flexible-joint manipulator. },
keywords = {Fuzzy Control; Lyapunov function; anti-control; Lorenz chaotic system; synchronization; Flexible joint; },
language = {English}
}

This study proposes a novel chaotic anti-control for flexible joint system. The proposed controller is composed of a Lyapunov rule-based fuzzy control and chaotic anti-control for target tracking of the flexible joint manipulator. Chaotic signal is used to study the effect of anti-control to reduce the deflection of flexible joint system and control signal energy. For this purposes the flexible joint has been synchronized with chaotic Lorenz system. In this study on of the Lorenz parameters is changed to analysis the effect of chaotic signals. The results of the proposed approach shows in terms of level of vibration reduction and energy consumption of control signal, we could find an optimum point based on value of Lorenz system parameter. Finally, the efficacy of the proposed method and results of existence of different nonlinearity behavior is validated through experiments on QUANSER’s flexible-joint manipulator.

@article{Qin2013a,
title = {Sliding mode control experiments of uncertain dynamical systems with time delay},
author = {Zhi-Chang Qin and Shun Zhong and Jian-Qiao Sun},
journal = {Communications in Nonlinear Science and Numerical Simulation},
year = {2013},
volume = {18},
institution = {Department of Mechanics, Tianjin University, Tianjin 300072, China},
abstract = {This article presents the simulation and experimental studies for the nonlinear time-delayed dynamical systems with uncertainties. A rotary flexible joint made by Quanser is chosen as the model system to investigate the method for sliding mode control design. We considered the geometric nonlinearity of the flexible joint consisting of two linear springs. The system is assumed to have constant delay time and uncertain parameters with known upper and lower bounds. We also design an optimal sliding surface for the sliding mode control. Simulations and experiments are carried out to demonstrate the utility of the control method. Finally, the results from the simulations and experiments are in excellent agreement. },
annotation = {jqsun@ucmerced.edu (J.-Q. Sun)},
keywords = {Nonlinear system; Time delay; Stability; Sliding mode control; Uncertainty},
pages = {3558--3566}
}

This article presents the simulation and experimental studies for the nonlinear time-delayed dynamical systems with uncertainties. A rotary flexible joint made by Quanser is chosen as the model system to investigate the method for sliding mode control design. We considered the geometric nonlinearity of the flexible joint consisting of two linear springs. The system is assumed to have constant delay time and uncertain parameters with known upper and lower bounds. We also design an optimal sliding surface for the sliding mode control. Simulations and experiments are carried out to demonstrate the utility of the control method. Finally, the results from the simulations and experiments are in excellent agreement.

@article{Kandroodi2012,
title = {Control of Flexible Joint Manipulator via Reduced Rule-Based Fuzzy Control with Experimental Validation},
author = {Rostami Kandroodi, M. and Mansouri, M. and Aliyari Shoorehdeli, M.and Teshnehlab, M.},
journal = {ISRN Artificial Intelligence},
year = {2012},
abstract = {A novel structure of fuzzy logic controller is presented for trajectory tracking and vibration control of a flexible joint manipulator. The rule base of fuzzy controller is divided into two sections. Each section includes two variables. The variables of first section are the error of tip angular position and the error of deflection angle, while the variables of second section are derivatives of mentioned errors. Using these structures, it would be possible to reduce the number of rules. Advantages of proposed fuzzy logic are low computational complexity, high interpretability of rules, and convenience in fuzzy controller. Implementing of the fuzzy logic controller on Quanser flexible joint reveals efficiency of proposed controller. To show the efficiency of this method, the results are compared with LQR method. In this paper, experimental validation of proposed method is presented. },
issn = {2090-7435},
keywords = {computational complexity;fuzzy control;fuzzy logic;knowledge based systems;manipulators;trajectory control;vibration control;},
address = {USA}
}

A novel structure of fuzzy logic controller is presented for trajectory tracking and vibration control of a flexible joint manipulator. The rule base of fuzzy controller is divided into two sections. Each section includes two variables. The variables of first section are the error of tip angular position and the error of deflection angle, while the variables of second section are derivatives of mentioned errors. Using these structures, it would be possible to reduce the number of rules. Advantages of proposed fuzzy logic are low computational complexity, high interpretability of rules, and convenience in fuzzy controller. Implementing of the fuzzy logic controller on Quanser flexible joint reveals efficiency of proposed controller. To show the efficiency of this method, the results are compared with LQR method. In this paper, experimental validation of proposed method is presented.

@inproceedings{pedram_feedback_2011,
title = {Feedback linearization and chaotic anti-control of flexible joint manipulator with Experimental validation},
author = {Pedram, M.Z. and Farivar, F. and Shoorehdeli, M.A.},
booktitle = {2nd International Conference on Control, Instrumentation and Automation(ICCIA)},
year = {2011},
institution = {Faculty of Electrical Engineering. Department of Mechatronics Engineering.K.N. Toosi University of Technology, Tehran, Iran.},
abstract = {This paper presents a feedback linearization and chaotic anti-control for trajectory tracking and vibration control of a flexible joint manipulator. To study the effectiveness of the controllers, designed controller is developed for tip angular position control of a flexible joint manipulator. Based on Lyapunov stability theory for variable structure control, the nonlinear controller and some generic sufficient conditions for global asymptotic control are attained. Also in this study, the anti-control is applied to reduce the deflection angle of flexible joint system. To achieve this goal, the chaos dynamic must be created in the flexible joint system. So, the flexible joint system has been synchronized to chaotic gyroscope system. In this study, control and anti-control concepts are applied to achieve the high quality performance of flexible joint system. It is tried to design a controller which is capable to satisfy the control and anti-control aims. The performances of the proposed control are examined in terms of input tracking capability, level of vibration reduction and time response specifications. Finally, the efficacy of the proposed method is validated through experimentation on QUANSER's flexible-joint manipulator. },
annotation = {pedram@ee.kntu.ac.ir},
keywords = {anticontrol, asymptotic stability, Automation, chaos, chaos dynamic,chaotic anticontrol, Chaotic gyroscope, chaotic gyroscope system,control system synthesis, deflection angle, designed controller,experimental validation, Feedback, Feedback linearization, Flexible joint, flexible joint manipulator, flexible joint system, flexible manipulators, generic sufficient conditions, global asymptotic control,gyroscopes, input tracking capability, Instruments, linearisation techniques, Lyapunov methods, Lyapunov stability theory, Nonlinear Control, nonlinear control systems, nonlinear controller, qualityperformance, QUANSER flexible-joint manipulator, synchronization,time response specifications, tip angular position control, trajectory control, trajectory tracking, Variable Structure Control, variable structure systems, vibration control, vibration reduction level},
pages = {841--846}
}

This paper presents a feedback linearization and chaotic anti-control for trajectory tracking and vibration control of a flexible joint manipulator. To study the effectiveness of the controllers, designed controller is developed for tip angular position control of a flexible joint manipulator. Based on Lyapunov stability theory for variable structure control, the nonlinear controller and some generic sufficient conditions for global asymptotic control are attained. Also in this study, the anti-control is applied to reduce the deflection angle of flexible joint system. To achieve this goal, the chaos dynamic must be created in the flexible joint system. So, the flexible joint system has been synchronized to chaotic gyroscope system. In this study, control and anti-control concepts are applied to achieve the high quality performance of flexible joint system. It is tried to design a controller which is capable to satisfy the control and anti-control aims. The performances of the proposed control are examined in terms of input tracking capability, level of vibration reduction and time response specifications. Finally, the efficacy of the proposed method is validated through experimentation on QUANSER's flexible-joint manipulator.

@article{pedram_2011,
title = {Hybrid Concepts of the Control and Anti-Control of Flexible Joint Manipulator},
author = {Pedram, M.Z.; Aliyari Shoorehdeli, M.; Farivar, F.; Kandsroodid, M.R.},
journal = {International Journal of Robotics (Theory and Application)},
year = {2011},
volume = {2},
number = {1},
abstract = {This paper presents a Gaussian radial basis function neural network based on sliding mode control for trajectory tracking and vibration control of a flexible joint manipulator. To study the effectiveness of the controllers, designed controller is developed for tip angular position control of a flexible joint manipulator. The adaptation laws of designed controller are obtained based on sliding mode control methodology without calculating the Jacobian of the flexible joint system. Also in this study, the anti-control is applied to reduce the deflection angle of flexible joint system. To achieve this goal, the chaos dynamic must be created in the flexible joint system. So, the flexible joint system has been synchronized to chaotic gyroscope system. In this study, control and anti-control concepts are applied to achieve the high quality performance of flexible joint system. It is tried to design a controller which is capable to satisfy the control and anti- control aims. The performances of the proposed control are examined in terms of input tracking capability, level of vibration reduction and time response specifications. Finally, the efficacy of the proposed method is validated through experimentation on QUANSERÍs flexible-joint manipulator. },
issn = {2008-7144},
keywords = {Gaussian RBF neural network, Sliding mode control, Switching surface, Anti-control, Chaos, Synchronization, Flexible Joint, Chaotic Gyroscope},
language = {English},
pages = {35-44}
}

This paper presents a Gaussian radial basis function neural network based on sliding mode control for trajectory tracking and vibration control of a flexible joint manipulator. To study the effectiveness of the controllers, designed controller is developed for tip angular position control of a flexible joint manipulator. The adaptation laws of designed controller are obtained based on sliding mode control methodology without calculating the Jacobian of the flexible joint system. Also in this study, the anti-control is applied to reduce the deflection angle of flexible joint system. To achieve this goal, the chaos dynamic must be created in the flexible joint system. So, the flexible joint system has been synchronized to chaotic gyroscope system. In this study, control and anti-control concepts are applied to achieve the high quality performance of flexible joint system. It is tried to design a controller which is capable to satisfy the control and anti- control aims. The performances of the proposed control are examined in terms of input tracking capability, level of vibration reduction and time response specifications. Finally, the efficacy of the proposed method is validated through experimentation on QUANSERÍs flexible-joint manipulator.

@article{talole_extended-state-observer-based_2010,
title = {Extended-State-Observer-Based Control of Flexible-Joint System With Experimental Validation},
author = {Talole, S. E.},
journal = {2010 IEEE Transactions on Industrial Electronics},
year = {2010},
volume = {57},
number = {4},
abstract = {In this paper, a feedback linearization (FL)-based control law made implementable using an extended state observer (ESO) is proposed for the trajectory tracking control of a flexible-joint robotic system. The FL-based controller cannot be implemented unless the full transformed state vector is available. The design also requires exact knowledge of the system model making the controller performance sensitive to uncertainties. To address these issues, an ESO is designed, which estimates the state vector, as well as the uncertainties in an integrated manner. The FL controller uses the states estimated by ESO, and the effect of uncertainties is compensated by augmenting the FL controller with the ESO-estimated uncertainties. The closed-loop stability of the system under the proposed observer-controller structure is established. The effectiveness of the ESO in the estimation of the states and uncertainties and the effectiveness of the FL + ESO controller in tracking are demonstrated through simulations. Lastly, the efficacy of the proposed approach is validated through experimentation on Quanser's flexible-joint module. },
issn = {2780046},
keywords = {vectors, closed loop systems, flexible manipulators, linearisation techniques, observers, position control, stability, state feedback, Quanser flexible joint module, extended state observer based control, feedback linearization based control law, trajectory tracking control, flexible joint robotic system, state vector, closed loop stability, observer controller structure, Control systems, Manipulator dynamics, Uncertainty, State estimation, Aerodynamics, Trajectory, Observers, Service robots, Elasticity, State feedback, flexible-joint system, Extended state observer (ESO) feedback linearization (FL)},
pages = {1411--1419}
}

In this paper, a feedback linearization (FL)-based control law made implementable using an extended state observer (ESO) is proposed for the trajectory tracking control of a flexible-joint robotic system. The FL-based controller cannot be implemented unless the full transformed state vector is available. The design also requires exact knowledge of the system model making the controller performance sensitive to uncertainties. To address these issues, an ESO is designed, which estimates the state vector, as well as the uncertainties in an integrated manner. The FL controller uses the states estimated by ESO, and the effect of uncertainties is compensated by augmenting the FL controller with the ESO-estimated uncertainties. The closed-loop stability of the system under the proposed observer-controller structure is established. The effectiveness of the ESO in the estimation of the states and uncertainties and the effectiveness of the FL + ESO controller in tracking are demonstrated through simulations. Lastly, the efficacy of the proposed approach is validated through experimentation on Quanser's flexible-joint module.

@article{gunnarsson_2007,
title = {On the use of accelerometers in iterative learning control of a flexible robot arm},
author = {Gunnarsson, S.; Norrlof, M.; Rahic, E.; Ozbek, M.},
journal = {International Journal of Control},
year = {2007},
volume = {80},
number = {3},
institution = {Linkoping University, Sweden},
abstract = {Iterative learning control (ILC) is applied to a robot arm with joint flexibility. The ILC algorithm uses an estimate of the arm angle, where the estimate is computed using measurements of the motor angle and the arm angular acceleration. The design of the ILC algorithm is evaluated experimentally on a laboratory scale robot arm with good results. },
language = {English},
publisher = {Taylor & Francis Online},
pages = {363-373}
}

Iterative learning control (ILC) is applied to a robot arm with joint flexibility. The ILC algorithm uses an estimate of the arm angle, where the estimate is computed using measurements of the motor angle and the arm angular acceleration. The design of the ILC algorithm is evaluated experimentally on a laboratory scale robot arm with good results.

@inproceedings{bhaskaran_2007,
title = {Practical Tuning of Fractional Order Proportional and Integral Controller (II): Experiments},
author = {Bhaskaran, Tripti; Chen, YangQuan; and Bohannan, Gary},
booktitle = {Proceedings of ASME IDETC/CIE 2007},
year = {2007},
abstract = {This paper aims to apply the practical tuning procedure for fractional order proportional and integral controller (FO-PI) to two experimental platforms. The first platform is QuanserÍs Heat Flow Experiment (HFE) and the second platform is the QuanserÍs Rotary Flexible Joint (RFJ) Module. The fractional controllers in both cases have been digitally implemented using OustaloupÍs recursive approximation. The second system however can also be controlled with the Fractroller which uses the novel element Fractor. Practical issues are introduced and discussed and interesting experimental results are reported that could serve as sample applications of the proposed FO-PI tuning rules. },
language = {English},
publisher = {ASME},
isbn = {0-7918-4806-X},
pages = {1371-1384}
}

This paper aims to apply the practical tuning procedure for fractional order proportional and integral controller (FO-PI) to two experimental platforms. The first platform is QuanserÍs Heat Flow Experiment (HFE) and the second platform is the QuanserÍs Rotary Flexible Joint (RFJ) Module. The fractional controllers in both cases have been digitally implemented using OustaloupÍs recursive approximation. The second system however can also be controlled with the Fractroller which uses the novel element Fractor. Practical issues are introduced and discussed and interesting experimental results are reported that could serve as sample applications of the proposed FO-PI tuning rules.

@article{albertos_2006,
title = {Phase-conditionally stable systems},
author = {Albertos, P.},
journal = {Systems & Control Letters},
year = {2006},
volume = {55},
number = {10},
institution = {Universidad Politecnica de Valencia, Spain},
abstract = {In this paper, the phase-conditionally stable feature of a closed-loop system is introduced. In any control loop, time delays appear and can produce unexpected changes in the controlled-system performances. Usually, these effects are negative and performance is degraded. The possible positive effect of the delays in avoiding oscillatory plant response is here considered. For that purpose, the effect of additional measurement delays, filters or dead time in resonant systems, is analyzed. Some examples illustrate the results. Other than the possible practical relevance of the results, the concepts involved are very important for the control engineers at educational level. },
keywords = {Time delays; Stabilizing delays; Performance degrading; Decoupling; Computing time delay},
language = {English},
publisher = {Elsevier B.V.},
pages = {803_808}
}

In this paper, the phase-conditionally stable feature of a closed-loop system is introduced. In any control loop, time delays appear and can produce unexpected changes in the controlled-system performances. Usually, these effects are negative and performance is degraded. The possible positive effect of the delays in avoiding oscillatory plant response is here considered. For that purpose, the effect of additional measurement delays, filters or dead time in resonant systems, is analyzed. Some examples illustrate the results. Other than the possible practical relevance of the results, the concepts involved are very important for the control engineers at educational level.

@conference{osterholt_2006,
title = {Virtual control workstation design using simulink, simmechanics, and the virtual reality toolbox},
author = {Osterholt, K.; Vaccari, A.; Faivre, J.; Dempsey, G.},
booktitle = {2006 ASEE Annual Conference & Exposition},
year = {2006},
institution = {Caterpillar Incorporated, USA; Bradley University, USA},
abstract = {Control workstations are used in education to teach control theory principles as well as a test station for control algorithm development. Two workstations from Quanser Consulting are being used in our electrical and computer engineering program in student projects. Additional workstations have not been purchased for students in the control theory courses because of cost and space constraints. However, incorporating a laboratory feel into these courses would enhance learning and retention. The design and use of a low-cost virtual control workstation in the first undergraduate control theory course will be discussed. The virtual workstation was modeled from the physical electrical and mechanical parameters of a Quanser Consulting electromechanical system. },
language = {English}
}

Control workstations are used in education to teach control theory principles as well as a test station for control algorithm development. Two workstations from Quanser Consulting are being used in our electrical and computer engineering program in student projects. Additional workstations have not been purchased for students in the control theory courses because of cost and space constraints. However, incorporating a laboratory feel into these courses would enhance learning and retention. The design and use of a low-cost virtual control workstation in the first undergraduate control theory course will be discussed. The virtual workstation was modeled from the physical electrical and mechanical parameters of a Quanser Consulting electromechanical system.

@article{Sheng2005,
title = {Feedback Controls and Optimal Gain Design of Delayed Periodic Linear Systems},
author = {Sheng, J and J. Q. Sun},
journal = {Journal of Vibration and Control},
year = {2005},
volume = {11},
number = {2},
abstract = {In this paper we present an application of a semi-discretization method to the stability analysis of PID feedback controls of linear systems with time delay. The method develops a mapping of the system response in a finite-dimensional state space. Minimization of the largest absolute value of the eigenvalues of the mapping leads to optimal control gains. Numerical examples of both time-invariant and periodic linear systems are presented to demonstrate the method. The tracking control problem of linear systems with time delay is also discussed. We have found that the semi-discretization method provides accurate stability boundaries and performance contours in the parametric space of control gains, and offers an alternative to the classic design approaches of feedback controls. },
keywords = {Semi-discretization, delayed feedback control, optimal feedback gains, root locus, time-delayed linear systems, Mathieu equation},
pages = {277--294}
}

In this paper we present an application of a semi-discretization method to the stability analysis of PID feedback controls of linear systems with time delay. The method develops a mapping of the system response in a finite-dimensional state space. Minimization of the largest absolute value of the eigenvalues of the mapping leads to optimal control gains. Numerical examples of both time-invariant and periodic linear systems are presented to demonstrate the method. The tracking control problem of linear systems with time delay is also discussed. We have found that the semi-discretization method provides accurate stability boundaries and performance contours in the parametric space of control gains, and offers an alternative to the classic design approaches of feedback controls.