Adaptive Controller for T-S Fuzzy Model with Modeling Error | Zendy

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Adaptive Controller for T-S Fuzzy Model with Modeling Error

Author(s) -

Hugang Han

Publication year - 2011

Publication title -

journal of advanced computational intelligence and intelligent informatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.172

H-Index - 20

eISSN - 1343-0130

pISSN - 1883-8014

DOI - 10.20965/jaciii.2011.p0759

Subject(s) - control theory (sociology) , computer science , controller (irrigation) , fuzzy logic , nonlinear system , bounded function , fuzzy control system , adaptive control , variable (mathematics) , adaptive neuro fuzzy inference system , mathematics , control (management) , artificial intelligence , mathematical analysis , physics , quantum mechanics , agronomy , biology

Modeling error occurs in linearizing the real (nonlinear) system into the (linear) T-S fuzzy model, and the existence of uncertainties in the real system including external disturbances. This paper deals with the T-S fuzzy model with modeling error in order to improve the control performance. As a result, an adaptive controller that consists of two parts: one is obtained by solving certain Linear Matrix Inequalities (LMIs) (fixed part) and the other is acquired by the fuzzy approximator in which the related parameters are tuned by adaptive law (variable part), is proposed. The proposed controller can guarantee all signals involved in the closed-loop system uniformly ultimately bounded.

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