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서지반출
Fuzzy Controller Design by Means of Genetic Optimization and NFN-Based Estimation Technique
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  • Fuzzy Controller Design by Means of Genetic Optimization and NFN-Based Estimation Technique
  • Fuzzy Controller Design by Means of Genetic Optimization and NFN-Based Estimation Technique
저자명
Oh. Sung-Kwun,Park. Seok-Beom,Kim. Hyun-Ki
간행물명
International Journal of Control, Automation and Systems
권/호정보
2004년|2권 3호|pp.362-373 (12 pages)
발행정보
제어로봇시스템학회
파일정보
정기간행물|ENG|
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이 논문은 한국과학기술정보연구원과 논문 연계를 통해 무료로 제공되는 원문입니다.
서지반출

기타언어초록

In this study, we introduce a noble neurogenetic approach to the design of the fuzzy controller. The design procedure dwells on the use of Computational Intelligence (CI), namely genetic algorithms and neurofuzzy networks (NFN). The crux of the design methodology is based on the selection and determination of optimal values of the scaling factors of the fuzzy controllers, which are essential to the entire optimization process. First, tuning of the scaling factors of the fuzzy controller is carried out, and then the development of a nonlinear mapping for the scaling factors is realized by using GA based NFN. The developed approach is applied to an inverted pendulum nonlinear system where we show the results of comprehensive numerical studies and carry out a detailed comparative analysis.