Proceedings of the KIEE Conference (대한전기학회:학술대회논문집)

The Korean Institute of Electrical Engineers (대한전기학회)
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Fuzzy Modeling for Nonlinear Systems Using Virus-Evolutionary Genetic Algorithm

바이러스-진화 유전 알고리즘을 이용한 비선형 시스템의 퍼지모델링

  • Lee, Seung-Jun (Dept. of Electrical & Computer Engineering, Yonsei Univ.) ;
  • Joo, Young-Hoon (Dept. of Control & Instrumentation Engineering, Kunsan National Univ.) ;
  • Chang, Wook (Dept. of Electrical & Computer Engineering, Yonsei Univ.) ;
  • Park, Jin-Bae (Dept. of Electrical & Computer Engineering, Yonsei Univ.)
  • 이승준 (연세대 전기. 컴퓨터공학과) ;
  • 주영훈 (군산대 제어계측공학과) ;
  • 장욱 (연세대 전기. 컴퓨터공학과) ;
  • 박진배 (연세대 전기. 컴퓨터공학과)
  • Published : 1999.07.19
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Abstract

This paper addresses the systematic approach to the fuzzy modeling of the class of complex and uncertain nonlinear systems. While the conventional genetic algorithm (GA) only searches the global solution, Virus-Evolutionary Genetic Algorithm(VEGA) can search the global and local optimal solution simultaneously. In the proposed method the parameter and the structure of the fuzzy model are automatically identified at the same time by using VEGA. To show the effectiveness and the feasibility of the proposed method, a numerical example is provided. The performance of the proposed method is compared with that of conventional GA.

Keywords