Observer-based fuzzy adaptive prescribed performance tracking control for nonlinear stochastic systems with input saturation

In this paper, the problem of prescribed performance adaptive fuzzy output feedback control is investigated for a class of single-input and single-output nonlinear stochastic systems with input saturation and unmeasured states. Fuzzy logic systems are used to identify the unknown nonlinear system, the input saturation is approximated by a smooth function, and a fuzzy state observer is designed for estimating the unmeasured states. Based on the backstepping recursive design technique and the predefined performance technique, a new fuzzy adaptive output feedback control method is developed. It is shown that all the signals of the resulting closed-loop system are bounded in probability and the tracking error remains an adjustable neighborhood of the origin with the prescribed performance bounds. The simulation example and the comparative results are provided to show the effectiveness of the proposed control approach.