Observer based policy iteration algorithm for fault tolerant control of nonlinear systems with actuator faults

Abstract

This paper investigates a novel fault tolerant control scheme to handle actuator faults in nonlinear systems based on policy iteration algorithm with fault observer. The fault observer is established to estimate the actuator fault, which is used to construct an improved performance index function that reflects the fault, regulation and control simultaneously. With the help of the proper performance index function, the FTC problem is transformed into an optimal control problem. By constructing a critic neural network, the Hamilton-Jacobi-Bellman equation can be solved by using policy iteration algorithm, and then the approximated fault tolerant controller can be obtained directly. The closed-loop system is guaranteed to be uniformly ultimately bounded based on the Lyapunov's direct method. Simulation example is given to verify the effectiveness of the developed FTC scheme.