Adaptive Fuzzy Output-Feedback Event-Triggered Command-Filtered Backstepping Control for Uncertain Discrete-Time Nonlinear Systems

This paper proposes an adaptive fuzzy output-feedback event-triggered control approach for uncertain discrete-time nonlinear systems with mismatched disturbances. The noncausal problem in traditional discrete-time backstepping can be effectively solved by introducing a command filter into each design step, and the influence of filtering error can be reduced by building an error compensation mechanism. Based on the approximation characteristics of the fuzzy logic systems, the fuzzy state observer is established to obtain the estimation of the immeasurable states although the uncertain dynamics exist. Furthermore, the adaptive update laws are designed for the observer to estimate unknown parameters, and the adaptive controller is developed under the event-triggered mechanism with a dynamic threshold to alleviate the network communication load. The stability analysis of the closed-loop systems is accomplished by constructing weighted Lyapunov functions, excluding Zeno behavior. The validity of the proposed control approach is demonstrated by simulation results.