Dynamic event-triggered fault-tolerant control for nonlinear systems via critic learning

This paper proposes a dynamic event-triggered fault-tolerant control strategy for affine nonlinear systems subject to actuator faults. The approach integrates a critic learning framework to approximate the optimal control policy with an adaptive fault compensation mechanism to mitigate actuator faults in real time, eliminating the need for fault detection and isolation. A dynamic event-triggered mechanism updates the control input, significantly reducing communication between the controller and the plant compared to static event-triggered or periodic control methods. Lyapunov-based analysis guarantees the asymptotic stability of the closed-loop system under actuator faults and event-triggered dynamics. Simulation results validate the approach, demonstrating effective fault compensation and reduced communication overhead compared to existing methods. The primary contribution lies in combining dynamic event-triggered control with critic learning to achieve efficient, stable, and adaptive FTC for nonlinear systems.