A Novel Fuzzy Model-Reference Adaptive Control

The paper presents a general methodology of adaptive control based on fuzzy model to deal with unknown nonlinear plants. The problem of parameter estimation is solved using a direct approach, i.e. the controller parameters are adapted without explicitly estimating plant parameters. Thus, very simple adaptive and control laws are obtained using Lyapunov stability criterion. The generality of the approach is substantiated by Stone-Weierstrass theorem, which indicates that any continuous function can be approximated by fuzzy basis function expansion. In the sense of adaptive control, this implies the adaptive law with fuzzified adaptive control parameters. The global stability of the control system is assured and the tracking error converges to the residual set that depends on fuzzification properties. The simulation results showed that the proposed approach has high adaptation ability and consequently good performance for nonlinear system