Command filtered adaptive fuzzy tracking control for uncertain stochastic nonlinear systems with event-triggered input

This paper addressed an issue regarding adaptive fuzzy backstepping for a class of stochastic nonlinear system with an event-triggered input. The presence of unknown nonlinear functions can be evaluated through fuzzy logic systems. With the aid of dynamic surface control, an adaptive tracking scheme is suggested, which can eliminate the “explosion of complexity.”An improved event-triggered co-design control scheme is proposed, whose threshold is a variable function combining tracking error, so that resources are saved. A tracking controller can guarantee that the signals of the closed-loop system are uniform. The tracking errors toward a small neighborhood of the origin. Simulations are conducted to validate the proposed method.