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In this paper, the event-triggered fixed-time control scheme is developed for a class of stochastic nonlinear systems with prescribed boundary constraints and actuator faults. For the controlled systems with unknown nonlinear functions, the neural networks are employed to reestablish the system model. Based on the event-triggered control technology, an original adaptive fixed-time control strategy with prescribed performance and the fault state is proposed by using the backstepping technique. Under the developed adaptive controller, the tracking error satisfies the predefined boundary functions and all the closed-loop system signals are bounded in probability in a fixed time, and the convergence time is irrelevant to the initial states of the system. The practicability of the designed controller is illustrated by a simulation example.

Event-triggered-based fixed-time adaptive prescribed tracking control for stochastic nonlinear systems with actuator faults