Fuzzy predictive control based on Takagi-Sugeno model for nonlinear systems

Abstract

In this paper, a method of designing a nonlinear predictive controller based on a fuzzy model of the system is presented. The Takagi-Sugeno fuzzy model is used as a powerful structure for representing nonlinear dynamic systems. So, the strategy of the fuzzy predictive control based on a fuzzy Takagi-Sugeno model is applied to the control of a chemical reactor. Indeed, the work is consists to develop, in a first step, a fuzzy model from a merger of a number of local models obtained by the principle of linearization around an operating point, or by learning through the gradient algorithm. In a second stage and basis on local models already developed, a fuzzy predictive control is synthesized with different approaches. The principal aim is to apply local generalized predictive control.