Observer-Based Fuzzy Adaptive Hybrid Control for Nonlinear Systems with Output Constraint

Abstract

This paper investigates the hybrid control problem for a class of single-input and single-output nonlinear system with output constraint. Fuzzy logic systems are used to approximate unknown nonlinear functions, and a fuzzy adaptive state observer is designed to estimate unmeasured states in the control design. A serial–parallel estimation model is established to improve identification accuracy. To address the problems of output constraint, the barrier Lyapunov function is constructed, and a new adaptive fuzzy output feedback hybrid control approach is proposed. The proposed control strategy guarantees that all the signals of the closed-loop system are semi-global uniform ultimate bounded, and tracking error converges to a small neighborhood of the origin. Finally, a simulation example is provided to illustrate the effectiveness of the presented control scheme.