Dynamic Event-Triggered Adaptive Fixed-Time Fuzzy Tracking Control for Stochastic Nonlinear Systems Under Asymmetric Time-Varying State Constraints

In this article, an adaptive fixed-time tracking control scheme is investigated for stochastic nonlinear systems with asymmetric time-varying state constraints based on the dynamic event-triggered control (DETC) mechanism. First, a unified barrier function is employed to constrain the states into asymmetric time-varying functions directly. Then, through fuzzy logic systems (FLS) and DETC strategy, the issues of unknown nonlinear functions and computation burden are solved. Meanwhile, with the aid of backstepping technology and Lyapunov stability theory, it is proved that all state variables are successfully within the asymmetric time-varying functions and all signals in the closed-loop systems are bounded in a fixed time. In the final, two simulation experiments illustrate the feasibility and suitability of the controller.