Adaptive Fuzzy Tracking Control for a Class of Uncertain Nonlinear Systems With Improved Prescribed Performance
Faxiang Zhang, Pengshuai Dai, Jing Na, Guanbin Gao, Yu Shi, Fei Liu
Abstract
This article addresses the tracking control problem of uncertain nonlinear strict-feedback systems. First, to enhance the tracking performance of control system, an improved prescribed performance function (PPF) is constructed, which yields that the convergence accuracy of tracking error can reach a preset factor than that of the traditional PPF-based control method. Then, the fuzzy logic system (FLS) is used to approximate the unknown nonlinear dynamics on a compact set integrated by an ideal controller, from which an adaptive fuzzy control law is designed by combining the improved PPF and FLS. The stability of closed-loop system and the convergence of tracking error are analyzed in the Lyapunov sense. Finally, simulation and experimental results show the feasibility and effectiveness of the proposed method.