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Optimal Auto-tuning of Fuzzy control rules by means of Genetic Algorithm

  • 김중영 (원광대학교 전기전자공학부) ;
  • 이대근 (원광대학교 전기전자공학부) ;
  • 오성권 (원광대학교 전기전자공학부) ;
  • 장성환 (원광대학교 전기전자공학부)
  • Kim, Joong-Young (Division of Electrical & Electronic Engineering, Wonkwang Univ.) ;
  • Lee, Dae-Keun (Division of Electrical & Electronic Engineering, Wonkwang Univ.) ;
  • Oh, Sung-Kwun (Division of Electrical & Electronic Engineering, Wonkwang Univ.) ;
  • Jang, Sung-Whan (Division of Electrical & Electronic Engineering, Wonkwang Univ.)
  • 발행 : 1999.11.20

초록

In this paper the design method of a fuzzy logic controller with a genetic algorithm is proposed. Fuzzy logic controller is based on linguistic descriptions(in the form of fuzzy IF-THEN rules) from human experts. The auto-tuning method is presented to automatically improve the output performance of controller utilizing the genetic algorithm. The GA algorithm estimates automatically the optimal values of scaling factors and membership function parameters of fuzzy control rules. Controllers are applied to the processes with time-delay and the DC servo motor. Computer simulations are conducted at the step input and the output performances are evaluated in the ITAE.

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