Robust Adaptive Fuzzy Fault Tolerant Control of Robot Manipulators With Unknown Parameters

Abstract

This paper resolves the safety tracking problem of the robot manipulator with the actuator faults, process faults, uncertain dynamics, and external disturbances. A novel robust adaptive fuzzy fault tolerant control (FTC) framework is presented. In this approach, a constraint mechanism of the zero overshoot error is proposed to keep the filter variable within an adjustable range, and the compact set can be available. An adaptive fuzzy logic system (FLS) is, then, employed to approximate the time-varying, nonlinear, and unknown robot dynamics. Furthermore, a robust adaptive term is designed to compensate the actuator faults and approximation errors, and ensure the convergence and stability of the whole robot control system. The uniform ultimate boundedness of the closed-loop dynamics for the robot manipulator is proved by the Lyapunov function. Afterwards, the simulation results demonstrate that the proposed robust adaptive fuzzy FTC (RAFFTC) approach of the robot manipulator has good control performance. Finally, the effectiveness of the proposed RAFFTC approach is verified by experiments.