Analysis of Takagi-Sugeno Fuzzy Models in System Identification for Model-Based Control

S. Lee and G.G. Yen


TS fuzzy model, system identification, model based control, identifiability


This article analyzes Takagi-Sugeno (TS) fuzzy models in system identification for model-based controller design. TS fuzzy modelbased controls have been proposed to overcome the long-standing criticism of lack of stability of fuzzy controls. However, the application of these controllers is limited as TS fuzzy models for controller design can only be obtained by transformation of nonlinear mathematical models. The proposal that fuzzy controls be used as control methods for uncertain systems has deviated from the original intention of fuzzy control. In this work, we investigate the possibility of extending TS fuzzy model-based control into uncertain systems. We show the limitation of these control methods and clarify the gap between fuzzy model based-control and fuzzy model identification. For the identification of constant-affine state-space models, a subspace identification algorithm is proposed to identify the true local dynamics with zero initial conditions.

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