Optimized Fault-Tolerant Fixed-Time Control for Nonlinear Strict-Feedback Systems With Output Constraints

Focusing on the actuator fault and output constraints of a nonlinear strict-feedback system, a neural network-based optimized fixed-time controller is investigated in this paper. An optimized backstepping framework is adopted for controller design, where a critic–actor architecture is integrated to progressively approximate the optimal control policy. And the adaptive laws are developed to compensate for the disturbance and actuator failure. To address the output constraints, a nonlinear function related to these constraints is directly incorporated into the controller, thereby simplifying the computations. Furthermore, the fixed-time stability of the closed-loop system and each subsystem is analyzed, along with the fulfillment of output constraints. Lastly, the efficiency and correctness of the proposed algorithm are confirmed through two numerical simulations.