Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/1390
Title: Stable fuzzy controller design for uncertain nonlinear systems : genetic algorithm approach
Authors: Leung, Frank H. F.
Lam, H. K.
Tam, Peter K. S.
Lee, Yim-shu
Subjects: Computer simulation
Feedback control
Fuzzy sets
Genetic algorithms
Nonlinear control systems
System stability
Issue Date: 2003
Publisher: IEEE
Source: FUZZ-IEEE 2003 : proceedings of the 12th IEEE International Conference on Fuzzy Systems : Sunday 25 May-Wednesday 28 May, 2003, St. Louis, Missouri, USA, p. 500-505.
Abstract: This paper addresses the stable fuzzy controller design problem of nonlinear systems. The methodology is based on a fuzzy logic approach and the genetic algorithm (GA). In order to analyze the system stability, the TSK fuzzy plant model is employed to describe the dynamics of the nonlinear plant. A fuzzy controller is then developed 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 GA. An application example on stabilizing an inverted pendulum system will be given. Simulation and experimental results will be presented to verify the applicability of the proposed approach.
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Type: Conference Paper
URI: http://hdl.handle.net/10397/1390
ISBN: 0-7803-7810-5
Appears in Collections:EIE Conference Papers & Presentations

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