Wang Jingwen, Tian Jiawei, Zhang Xia, Yang Bo, Liu Shan, Yin Lirong, Zheng Wenfeng
School of Automation, University of Electronic Science and Technology of China, Chengdu, China.
Department of Geography and Anthropology, Louisiana State University, Baton Rouge, LA, United States.
Front Neurorobot. 2022 May 6;16:877069. doi: 10.3389/fnbot.2022.877069. eCollection 2022.
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.
为了使遥操作系统更具实用性，有效控制遥操作系统的跟踪误差收敛时间很有必要。通过将终端滑模控制方法与神经网络自适应控制方法相结合，为组合遥操作系统设计了一种双边连续有限时间自适应终端滑模控制方法。利用李雅普诺夫理论分析闭环系统的稳定性，位置跟踪误差能够及时有效地收敛。最后，通过MATLAB Simulink数值仿真验证了所提控制方案的有效性，结果的数值分析表明该方法具有更好的系统性能。与PD时延遥操作系统的传统双边控制方法（TPDC）相比，本文的控制方法具有良好的性能，提高了稳定性，使稳态误差更小且跟踪效果更好。
