Takagi-Sugeno model synthesis of a quasi-linear parameter varying mobile robot

Abstract

This paper presents the application of the Takagi-Sugeno (TS) model synthesis for a quasi-linear parameter varying (QLPV) four wheel differentially steered mobile robot. The focus of this paper is a mathematical description of the mobile robot model as a QLPV and application of the TS fuzzy logic framework which complements the QLPV approach. Using QLPV model data several local TS linear models were identified using recursively the subtractive clustering method with specified error criteria. The identified TS local models resulted in a family of LTI models, which are equivalent to the linearised QLPV models. The T-S blended model synthesis resulted in a close approximation to the non-linear model dynamics.