Adaptive Fuzzy Decentralized Output Feedback Control for Nonlinear Large-Scale Systems With Unknown Dead-Zone Inputs

Abstract

In this paper, the problem of adaptive fuzzy decentralized backstepping control is considered for a class of nonlinear large-scale strict-feedback systems with unknown dead zones and immeasurable states. Fuzzy logic systems are used to approximate the unknown nonlinear functions, and a state filter is designed to estimate the immeasurable states. Applying an adaptive backstepping design technique and combining it with the dead-zone inverse method, an adaptive fuzzy decentralized output-feedback backstepping control is developed. It is proved that all the signals of the resulting closed-loop adaptive control system are semiglobally uniformly ultimately bounded, and tracking errors converge to a small neighborhood of the origin by appropriate choice of design parameters. Simulation results are given to demonstrate that the proposed adaptive decentralized control approach has a satisfactory control performance.