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Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/1432

Title: Optimal and stable fuzzy controllers for nonlinear systems based on an improved genetic algorithm
Authors: Leung, Frank H. F.
Lam, H. K.
Ling, S. H.
Tam, Peter K. S.
Subjects: Fuzzy control
Nonlinear systems
Optimality and stability
Issue Date: Feb-2004
Publisher: IEEE
Citation: IEEE transactions on industrial electronics, Feb. 2004, v. 51, no. 1, p. 172-182.
Abstract: This paper addresses the optimization and stabilization problems of nonlinear systems subject to parameter uncertainties. The methodology is based on a fuzzy logic approach and an improved genetic algorithm (GA). The TSK fuzzy plant model is employed to describe the dynamics of the uncertain nonlinear plant. A fuzzy controller is then obtained to close the feedback loop. The stability conditions are derived. The feedback gains of the fuzzy controller and the solution for meeting the stability conditions are determined using the improved GA. In order to obtain the optimal fuzzy controller, the membership functions are further tuned by minimizing a defined fitness function using the improved GA. An application example on stabilizing a two-link robot arm will be given.
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This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.
Type: Journal/Magazine Article
URI: http://hdl.handle.net/10397/1432
ISSN: 0278-0046
Appears in Collections:EIE Journal/Magazine Articles

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