Command Filter-Based Adaptive Fault-Tolerant Controller Design For Nonstrict-Feedback Nonlinear Systems

This paper investigates the neural network adaptive control problem for a class of nonstrict-feedback nonlinear systems with nonaffine nonlinear faults. The command filter is used to solve the problem of complexity explosion. The adaptive fault-tolerant tracking controller is designed by using neural network approximation and Butterworth low-pass filter. The proposed control method in this paper can ensure that the tracking error converges to a small range near the origin, and all signals of the closed-loop system are bounded. Finally, a simulation example is given to illustrate the effectiveness of the proposed control method.