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Control of Time Delay Force Feedback Teleoperation System With Finite Time Convergence.
Wang, Jingwen; Tian, Jiawei; Zhang, Xia; Yang, Bo; Liu, Shan; Yin, Lirong; Zheng, Wenfeng.
Afiliación
  • Wang J; School of Automation, University of Electronic Science and Technology of China, Chengdu, China.
  • Tian J; School of Automation, University of Electronic Science and Technology of China, Chengdu, China.
  • Zhang X; School of Automation, University of Electronic Science and Technology of China, Chengdu, China.
  • Yang B; School of Automation, University of Electronic Science and Technology of China, Chengdu, China.
  • Liu S; School of Automation, University of Electronic Science and Technology of China, Chengdu, China.
  • Yin L; Department of Geography and Anthropology, Louisiana State University, Baton Rouge, LA, United States.
  • Zheng W; School of Automation, University of Electronic Science and Technology of China, Chengdu, China.
Front Neurorobot ; 16: 877069, 2022.
Article en En | MEDLINE | ID: mdl-35599666
ABSTRACT
In order to make the teleoperation system more practical, it is necessary to effectively control the tracking error convergence time of the teleoperation system. By combining the terminal sliding mode control method with the neural network adaptive control method, a bilateral continuous finite time adaptive terminal sliding mode control method is designed for the combined teleoperation system. The Lyapunov theory is used to analyze the stability of the closed-loop system, and the position tracking error is able to effectively converge in time. Finally, the effectiveness of the proposed control scheme is verified by MATLAB Simulink numerical simulation, and the numerical analysis of the results shows that the method has better system performance. Compared with the traditional two-sided control method (TPDC) of PD time-delay teleoperation system, the control method in this paper has good performance, improves stability, and makes steady-state errors smaller and better tracking.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Front Neurorobot Año: 2022 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Front Neurorobot Año: 2022 Tipo del documento: Article País de afiliación: China