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Robust adaptive fuzzy controller for non‐affine nonlinear systems with dynamic rule activation
Author(s) -
Park JangHyun,
Park GwiTae
Publication year - 2003
Publication title -
international journal of robust and nonlinear control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.361
H-Index - 106
eISSN - 1099-1239
pISSN - 1049-8923
DOI - 10.1002/rnc.717
Subject(s) - control theory (sociology) , fuzzy logic , fuzzy control system , nonlinear system , fuzzy rule , a priori and a posteriori , affine transformation , controller (irrigation) , computer science , mathematics , adaptive control , computation , adaptive neuro fuzzy inference system , robust control , mathematical optimization , algorithm , control (management) , artificial intelligence , philosophy , physics , epistemology , quantum mechanics , pure mathematics , agronomy , biology
This paper describes the design of a robust adaptive fuzzy controller for an uncertain single‐input single‐output nonlinear dynamical systems. While most recent results on fuzzy controllers considers affine systems with fixed rule‐base fuzzy systems, we propose a control scheme for non‐affine nonlinear systems and a dynamic fuzzy rule activation scheme in which an appropriate number of the fuzzy rules are chosen on‐line. By using the proposed scheme, we can reduce the computation time, storage space, and dynamic order of the adaptive fuzzy system without significant performance degradation. The Lyapunov synthesis approach is used to guarantee a uniform ultimate boundedness property for the tracking error, as well as for all other signals in the closed loop. No a priori knowledge of an upper bounds on the uncertainties is required. The theoretical results are illustrated through a simulation example. Copyright © 2002 John Wiley & Sons, Ltd.