An online fault-tolerant control approach based on policy iteration algorithm for nonlinear time-delay systems

This paper introduces an online fault-tolerant control method for nonlinear time-delay systems with actuator faults using a policy iteration algorithm. A new performance index function is proposed to account for time-delay states, from which control laws are derived. The approach combines policy iteration with a fault compensator, solving the Hamilton-Jacobi-Bellman equation associated with this innovative value function via a critic neural network. Actuator faults are reconstructed for online fault compensation without the need for fault detection and isolation. The Lyapunov functional analysis demonstrates the closed-loop system's asymptotic stability in the presence of actuator faults and time-delay states. Simulation results validate the effectiveness of the proposed fault compensation strategy. The key contribution of this paper is the incorporation of time-delay states into the value function of the policy iteration algorithm, addressing the problem of fault compensation in nonlinear time-delay systems.