Adaptive fuzzy tracking of switched nonstrict-feedback nonlinear systems with state constraints based on event-triggered mechanism

This paper is devoted to develop an adaptive fuzzy tracking control scheme for switched nonstrict-feedback nonlinear systems (SNFNS) with state constraints based on event-triggered mechanism. All state variables are ensured to keep the predefined regions by employing barrier Lyapunov function (BLF). The fuzzy logic systems are exploited to cope with the unknown dynamics existing the SNFNS. It proposes to mitigate data transmission and save communication source whereby the event-triggered mechanism. With the aid of Lyapunov stability analysis and the average dwell time (ADT) method, it is shown that all variables of the entire SNFNS are uniformly ultimate bounded (UUB) under switching signals. Finally, simulation studies are discussed to substantiate the validity of theoretical findings.