Observer-Based Adaptive Fuzzy Tracking Control for MIMO Nonlinear Systems with Asymmetric Time-Varying Constraints

This article studies the adaptive tracking control for a type of multi-input multi-output nonlinear systems, which still is an open issue coming from considerations of system uncertainties, unmeasurable states, and asymmetric time-varying full-state constraints. Fuzzy logic systems (FLSs) are trained online to estimate and compensate for unknown nonlinear system dynamics, effectively improving uncertainties rejection capabilities. To solve unmeasurable states, a state observer, including FLSs, is built and does provide a fairly good observation accuracy. Notably, an asymmetric time-varying barrier Lyapunov function is constructed to realize full-state constraint satisfactions. Based on the above theoretical findings, an adaptive fuzzy tracker is designed in a recursive manner. A Lyapunov analysis demonstrates the stability of the closed-loop system, and particularly, the constrained conditions will not be violated during the whole operation. Simulation results show the usefulness of the developed tracker.