Adaptive Fuzzy Control for Teleoperation System with Uncertain Kinematics and Dynamics

Yang, Liang; Chen, Yong; Liu, Zhi; Chen, Kairui; Zhang, Zixuan

doi:10.1007/s12555-017-0631-z

Cited by 23 publications

(13 citation statements)

References 26 publications

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“…To further evaluate the performance of the sliding mode observer-based control (SMOBC), it is compared with the adaptive fuzzy control (AFC) [38] and nonlinear adaptive bilateral control (NAC) [39] for teleoperation system with dynamic and kinematic uncertainties. Two indices are selected to compare the performance of the controllers, which are defined as…”

Section: Quantitative Analysismentioning

confidence: 99%

“…3) Take the uncertain dynamics and kinematics into consideration simultaneously in teleoperation system, in comparison with the estimation scheme in [37][38][39], the suggested sliding mode observers in this study can guarantee finite-time estimation. Moreover, the proposed controllers ensure that the tracking errors between local and remote robots converge to the arbitrary set close to the origin within finite time, with the faster convergence time realized.…”

Section: Introductionmentioning

confidence: 99%

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Sliding Mode Observer-based Control of Teleoperation System With Uncertain Dynamics and Kinematics

Zhang

Wang

Wen

2021

Preprint

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This paper concentrates on the control issue of nonlinear teleoperators in the presence of uncertain dynamics and kinematics. An observer-based control framework is introduced to compensate for the unfavorable effects arising from the uncertainties. The employment of the proposed sliding mode observers provide control system with the ability of finite-time estimation errors convergence, upon which, it is demonstrated that the bilateral teleoperators are stable and both of position and velocity tracking can be achieved with uncertain dynamics in joint space. Due to the practical requirement of driving the end-effectors to perform specific tasks, the control law which can ensure position coordination with uncertain dynamics and kinematics in task space is subsequently developed. The Lyapunov method is applied to demonstrate the stability of the closed-loop system. Simulation results are provided to testify the performance of the suggested algorithm.

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Section: Quantitative Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Sliding Mode Observer-based Control of Teleoperation System With Uncertain Dynamics and Kinematics

Zhang

Wang

Wen

2021

Preprint

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“…Here, x desired is the output we need from the device, and μ(t) is the output coming from the controller and going to each actual in addition to the mathematical model. The approach includes (i) Identification based learning and (ii) Fuzzy inferencing for control so the fuzzy logic control system can be adapted to the controlled system while the fuzzy logic controller simultaneously calculates and applies the control inputs to the system [18]. In Figure 2, the inner-loop achieves fuzzy logic identification (i) while the outer-loop performs fuzzy control (ii).…”

Section: ( ) ( ) ( ) E T X T Y T =−mentioning

confidence: 99%

Integrated Design of Adaptive & Fuzzy Logic Control for Trajectory Tracking of 2 DOF Quadrotor

Jibril

2021

Preprint

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Accurate and precise trajectory tracking is crucial for a quadrotor to operate in disturbed environments. This paper presents a novel tracking hybrid controller for a quadrotor UAV that combines the Adaptive and Fuzzy logic controller. The Adaptive fuzzy controller is implemented to govern the behavior of two degrees of freedom quadrotor UAV. The proposed controller allows controlling the movement of UAVs to track a given trajectory in a 2D vertical plane. The Fuzzy Logic system provides an automatic adjustment of the Adaptive parameters to reduce tracking errors and improve the quality of the controller. The results showed perfect behavior for the control law to control a quadrotor trajectory tracking task. To show the effectiveness of the intelligent controller, simulation results are given to confirm the advantages of the proposed control method, compared with Fuzzy and Proportional integral derivative (PID) control methods.

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“…Kebria et al 25 proposed and implemented a robust adaptive control scheme for the teleoperation system with time delay and parameter uncertainty. Yang et al 26 used an adaptive approach for monitoring control of a teleoperation system with kinematic and dynamic uncertainties. In this approach, they used the adaptive fuzzy control method to estimate the parameters of the system and to control the system.…”

Section: Introductionmentioning

confidence: 99%

Optimal adaptive computed torque control for haptic-teleoperation system with uncertain dynamics

Abut

Soygüder

2021

Proceedings of the Institution of Mechanical Engineers, Part I:

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This study aimed to eliminate dynamic uncertainty, one of the main problems of haptic teleoperation robotic systems. The optimal adaptive computed torque control method was used to overcome this problem. As is known, excellent stability and transparency are required in teleoperation systems. However, dynamic uncertainty that causes stability problems in the control of these systems also causes poor performance. In conventional adaptive computed torque control methods, updating the parameters of the system is generally discussed, but updating the control coefficients of vital importance in the control of the system is not considered. In the proposed method, an adaptation rule has been created to update uncertain parameters. In addition, the gray wolf optimization algorithm, one of the current optimization algorithms, has been proposed and applied to obtain the control coefficients of the system. The position tracking stability of the system was examined by using Lyapunov stability analysis method. As a result, both simulation and real-time optimal adaptive computational torque control method were used and bilateral position and force control was performed and the performance results of the system are obtained graphically and examined. Optimal adaptive computed torque control method obtained using the gray wolf optimization algorithm was used first in the literature search and success results have been obtained. In this regard, the authors have the idea that this work is an innovative aspect of both simulation and real time with the optimal adaptive computed torque control method.

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Adaptive Fuzzy Control for Teleoperation System with Uncertain Kinematics and Dynamics

Cited by 23 publications

References 26 publications

Sliding Mode Observer-based Control of Teleoperation System With Uncertain Dynamics and Kinematics

Sliding Mode Observer-based Control of Teleoperation System With Uncertain Dynamics and Kinematics

Integrated Design of Adaptive & Fuzzy Logic Control for Trajectory Tracking of 2 DOF Quadrotor

Optimal adaptive computed torque control for haptic-teleoperation system with uncertain dynamics

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