Event-triggered fixed-time adaptive fuzzy control for state-constrained stochastic nonlinear systems without feasibility conditions

The problem of event-triggered fixed-time control for state-constrained stochastic nonlinear systems is discussed in this article. Different from the barrier Lyapunov function (BLF)-based and Integral BLF-based schemes that rely on feasibility conditions (FCs), by introducing the nonlinear state-dependent functions, the asymmetric time-varying state constraints are handled without FCs. Combined with the fixed-time stability theory and the dynamic surface control technique with fixed-time filter, the fixed-time stability in probability of the closed-loop system is ensured and the problems of “explosion of complexity” and “singularity” are overcome. Furthermore, the novel fixed-time error compensation signals are designed to compensate the filtering errors, and the event-triggered control technique is used to save network resources. Simulations also illustrate the effectiveness of the proposed method.