Adaptive Fuzzy Event-Triggered Control for Non-Strict Feedback Nonlinear Systems With Input Delay and Full State Constraints

An event-triggered-based adaptive fuzzy control strategy is proposed for full state constraints nonlinear systems against time-varying disturbance, non-strict feedback structure, and input delay in this paper. Fuzzy logic systems (FLSs) are implemented to estimate the unknown nonlinear functions in the systems. The influence of input delay can be compensated by the method of Pade approximation, and the barrier Lyapunov function (BLF) is exploited to handle the problem of full state constraints. The input-to-state stability (ISS) assumption regarding measurement errors can be removed through the co-design of the event-triggered mechanism and the controller. Based on Lyapunov stability theory, all the signals in the closed-loop system are proved semi-globally uniformly ultimately bounded (SGUUB), and only a tiny tracking error between the system output and the reference signals, moreover, the Zeno behavior is avoided. The effectiveness of the adaptive control scheme can be verified by two simulation examples.