Adaptive fuzzy output feedback control for a class of nonlinear pure-feedback systems with full state constraints

This paper is concerned with the problem of adaptive fuzzy output feedback control for a class of nonlinear pure-feedback systems with full state constraints. Because the systems have immeasurable states, the fuzzy state observers are designed to estimate the unmeasured states with the help of fuzzy logic systems to approximate the unknown nonlinear functions. A fuzzy adaptive output feedback control scheme is developed by incorporating the filtered signals into the backstepping recursive design, which guarantees that the full state constraints are not violated. All the signals of the closed-loop systems are bounded after employing Barrier Lyapunov Function (BLF), and the observer errors and the tracking errors of the systems converge to a small neighborhood of the origin by choosing the appropriate design parameters. Simulation studies show the effectiveness of the proposed approach.