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An Indirect Adaptive Fuzzy Control Scheme for a Class of Nonlinear Systems
Author(s) -
Kar Indrani
Publication year - 2016
Publication title -
asian journal of control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.769
H-Index - 53
eISSN - 1934-6093
pISSN - 1561-8625
DOI - 10.1002/asjc.1195
Subject(s) - control theory (sociology) , controller (irrigation) , nonlinear system , mathematics , fuzzy control system , fuzzy logic , adaptive control , convergence (economics) , a priori and a posteriori , representation (politics) , estimator , tracking error , adaptive neuro fuzzy inference system , mathematical optimization , computer science , control (management) , artificial intelligence , physics , quantum mechanics , philosophy , statistics , epistemology , politics , economic growth , law , political science , agronomy , economics , biology
This paper presents an indirect adaptive control scheme, for a class of nonlinear systems in controller canonical form. Owing to the universal approximation property of a Takagi–Sugeno (T–S) fuzzy model, controller design is simplified by utilizing the T–S fuzzy model representation of a nonlinear system. An adaptation mechanism ensures that the estimator model asymptotically follow the actual T–S fuzzy model and thus removes the need of any a priori identification of the T–S fuzzy model of the system. The overall controller gain is a convex combination of the local linear gains which vary adaptively to ensure the convergence of the tracking error. Preliminary simulation results indicate the potential of the proposed method.

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