Design of robust adaptive fuzzy control for uncertain bilateral teleoperation systems based on backstepping approach

Abstract

In this study, a novel method based on a robust adaptive fuzzy control approach is developed for nonlinear teleoperation systems. Its main objectives are to ensure system stability and properly mitigating parametric uncertainties stemming from external disturbances and un‐modelled dynamics. For the communication channel, instead of the direct transmission of environmental torque signals, the approximated environmental parameters by the fuzzy system are transmitted to the master side for the prediction of environmental torque, thus successfully avoiding the transmission of the power signals in the delayed communication channel and solving the passivity problem in the teleoperation system. Besides, a trajectory generator is employed in the master side, whereas a trajectory smoothing is provided in the slave side. Theoretically, it was proven that both position tracking and force feedback problems are attained. Using Lyapunov stability analysis, this work illustrates that the robust adaptive fuzzy controller based on the backstepping approach guarantees the system's asymptotic stability. Simulation results confirm the efficiency of the suggested control technique in achieving the stability and tracking objectives of the uncertain nonlinear teleoperation system.

The Adaptive Bilateral Control of Underwater Manipulator Teleoperation System with Uncertain Parameters and External Disturbance

“…There is the time-delay problem in underwater communications, which may cause control delays and reduce the responsiveness of the system for remote operations with high real-time requirements. The robot is a time-varying, strongly coupled multi-input multi-output nonlinear system, and uncertainty is inevitable in practical applications [12]. Therefore, under the premise of ensuring the stability of the overall system, uncertainty teleoperation control improves transparency and robustness, and enables position and force signals to be reproduced synchronously on the slave manipulator and the master manipulator, which is still the overall control goal.…”

“…In order to solve the problems of model uncertainty and external disturbance in teleoperation control, many scholars have proposed different control methods. Numerous effective control schemes, including the adaptive bilateral control method [13,14], predictive control [15,16], optimal control [17], intelligent control based on fuzzy logic [12,18] or neural networks [19,20], prescribed-performance-based control [21,22], etc., have been developed for bilateral teleoperation systems in recent years. The adaptive neural network controller with an adaptive time-delay estimator and parameter adaptive method is designed for the precise position tracking in the teleoperation system under communication constraints [14].…”

H∞ control of a bilateral teleoperation system: Application to a PV system

“…This combination offers a flexible control approaches that can effectively handle uncertain dynamics. The T-S fuzzy control methodology provides a systematic framework for modeling and control design, allowing for the representation of teleoperation dynamics and the synthesis of robust control laws [17][18][19].…”