Command Filter-Based Adaptive Fault-Tolerant Control for Nonstrict-Feedback Nonlinear Systems

Abstract

This paper investigates the command filter-based adaptive fault-tolerant control for nonstrict-feedback nonlinear system with sensor faults and actuator constraints. The actuator nonlinearity is addressed by an equivalent transformation method, and the radial basis function neural network (RBFNN) is utilized to approximate unknown nonlinear function. Furthermore, to address the explosion of complexity, the command filter method is applied. Then, an adaptive fault-tolerant control strategy is developed. Based on this strategy, the output tracking error can converge to a small bounded area near the origin and the boundedness of all variables in the closed-loop system is guaranteed. Finally, control performance is verified by the simulations.