Event-Triggered Prescribed Time Adaptive Fuzzy Fault-Tolerant Control for Nonlinear Systems With Full-State Constraints

This work investigates the prescribed finite-time event-triggered control of uncertain nonlinear systems with full- state constraints and actuator failures. In order to approximate the unknown nonlinear dynamic function, the fuzzy logic system (FLS) is used in this paper. By integrating the backstepping design framework with Lyapunov stability theory, a novel event- triggered condition that incorporates a decreasing function of the system interstate error is proposed. The developed method not only confines tracking errors within a predetermined range within the prescribed setting time but also ensures that all states adhere to their respective constraints. Additionally, the approach effectively mitigates the impacts of the Zeno phenomenon and actuator failure. Simulation results on a mass- spring-damper system demonstrate the efficacy of the proposed method.