Stable fuzzy controller design for uncertain nonlinear systems: Genetic algorithm approach

Hung Fat Frank Leung; H. K. Lam; P. K.S. Tam; Y. S. Lee

Stable fuzzy controller design for uncertain nonlinear systems: Genetic algorithm approach

Hung Fat Frank Leung, H. K. Lam, P. K.S. Tam, Y. S. Lee

The Hong Kong Polytechnic University

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

4 Citations (Scopus)

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.

Original language	English
Title of host publication	IEEE International Conference on Fuzzy Systems
Pages	500-505
Number of pages	6
Publication status	Published - 11 Jul 2003
Event	The IEEE International conference on Fuzzy Systems - St. Louis, MO, United States Duration: 25 May 2003 → 28 May 2003

Conference

Conference	The IEEE International conference on Fuzzy Systems
Country/Territory	United States
City	St. Louis, MO
Period	25/05/03 → 28/05/03

ASJC Scopus subject areas

Software
Theoretical Computer Science
Artificial Intelligence
Applied Mathematics

More information

http://hdl.handle.net/10397/1390

Cite this

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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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AB - 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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ER -

Stable fuzzy controller design for uncertain nonlinear systems: Genetic algorithm approach

Abstract

Conference

ASJC Scopus subject areas

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