ADP-Based Fault-Tolerant Control with Stability Guarantee for Nonlinear Systems

This paper develops the stability-guaranteed adaptive dynamic programming (ADP)-based fault tolerant control (FTC) for nonlinear systems with an actuator fault. Firstly, a fault observer is designed to identify the unknown actuator fault. Then, a critic neural network (NN) is built to approximate the optimal control of the nominal system. Meanwhile, a stability-aware weight update mechanism is proposed based on the Lyapunov stability theorem to relax the restriction of the initial admissible control on the system stability. By integrating the nominal optimal control and the fault estimation, the stability-guaranteed ADP-based FTC is developed to eliminate the influence of the actuator fault. Furthermore, the observer errors, critic NN weight estimation errors, and the closed-loop system are all shown to exhibit uniform ultimate boundedness by using Lyapunov's direct method. Finally, simulation examples are given to demonstrate the validity of the proposed method.