Fuzzy‐based adaptive control design for stochastic nonlinear time‐delay systems via event‐triggered mechanism

Abstract

Summary This article elaborates an adaptive fuzzy event‐triggered control design for stochastic nonlinear time‐delay systems with full‐state constraints. The prescribed constraints are ensured by employing barrier Lyapunov function. The fuzzy logic systems are exploited to approximate lumped unknown nonlinear functions. By cleverly choosing Lyapunov–Krasovskii functional, the adverse effect of time‐delay is effectively overcome. Meanwhile, the event‐triggered mechanism is adopted to save communication resource. It is illustrated that all signals of the controlled system are bounded and all states are maintained the prescribed regions at every step of recursive backstepping design. Finally, simulation results elucidate the validity of the devised scheme.

Compound conditions event‐triggered tracking control for nonlinear multiagent systems with nonlinear output faults

“…If S i,1 (t) is a bounded function, then z i,1 (t) satisfies the prescribed performance form described by (15).…”

“…To tackle such a difficulty, many scholars try to use the event-triggered (ET) technology to solve this problem. [11][12][13][14][15][16][17][18][19][20] For example, Xing et al 21 dealt with a class of adaptive ET control problems and proposed the switching threshold strategy to effectively balance the system performance and the network constraint problems. In Reference 22, the authors proposed an ET mechanism of the nonlinear continuous-time systems, which based on the available state value and fuzzy weights information to set conditions.…”

“…To tackle such a difficulty, many scholars try to use the event‐triggered (ET) technology to solve this problem 11‐20 . For example, Xing et al 21 dealt with a class of adaptive ET control problems and proposed the switching threshold strategy to effectively balance the system performance and the network constraint problems.…”