T-S Model Based Indirect Adaptive Fuzzy Control for a Class of MIMO Uncertain Nonlinear Systems

Abstract

This paper presents a Takagi-Sugeno (T-S) fuzzy model based indirect adaptive control algorithm for a class of uncertain multiple-input-multiple-output (MIMO) nonlinear systems. The T-S model consisting of a set of affine fuzzy local models is used to model a nonlinear uncertain system. Local integral controllers are designed based on local affine fuzzy models corresponding to different operating points of the controlled nonlinear system. Local controllers are combined to generate an overall controller by using fuzzy weighted integration. The T-S fuzzy model is adaptive both in its structure and parameters. The structure of the T-S model varies when the nonlinear system moves to different operating regions and the membership and consequent parameters are updated online in the presence of external disturbances and parameter perturbations. Simulation results on tracking control of a two-link robot manipulator are given to illustrate the effectiveness of the proposed method.