INDIRECT ADAPTIVE FUZZY CONTROL FOR NONLINEAR SYSTEMS WITH ONLINE MODELLING

This paper presents an indirect adaptive fuzzy control scheme for a class of single-input-single-output (SISO) nonlinear systems. A Takagi-Sugeno (T-S) fuzzy model is employed as a dynamical model of the partially known nonlinear system. Both the structure and the parameters of the T-S model are identified on-line. A T-S model based feedback linearization controller (FLC) is designed and a Lyapunov based supervisory controller is appended to the FLC to force the tracking error to be within a bounded set. The stability of the system is established using Lyapunov approach and its performance is evaluated by the tracking control of a single-link robot manipulator.