Event-Triggered Adaptive Output Feedback Control for Stochastic Nonlinear Systems With Time-Varying Full-State Constraints

This brief investigates the issue of event-triggered adaptive output feedback control for stochastic nonlinear systems with time-varying full-state constraints. Firstly, the unmeasurable states are estimated by the fuzzy observer. Secondly, the quartic time-varying barrier Lyapunov functions are constructed to avoid the violation of time-varying constraints. Thirdly, the command filter technique and error compensation mechanism are incorporated into the controller design to get over the issue of "explosion of complexity" and compensate the filtered errors. Then, the event-triggered mechanism is introduced to improve the efficiency in resource utilization. It is shown that the tracking error can converge to the desired neighborhood of the origin and all the signals in the closed-loop systems are bounded. Finally, the validity of the control strategy is demonstrated by a physical example.