퍼지 추론 방법을 이용한 퍼지 동정과 유전자 알고리즘에 의한 이의 최적화

Fuzzy Identification by means of Fuzzy Inference Method and its Optimization by GA

  • 박병준 (원광대학교 제어계측공학과) ;
  • 박춘성 (원광대학교 제어계측공학과) ;
  • 안태천 (원광대학교 제어계측공학과) ;
  • 오성권 (원광대학교 제어계측공학과)
  • Park, Byoung-Jun (Dept. of Control & Instrumentation Engineering, Wonkwang Univ.) ;
  • Park, Chun-Seong (Dept. of Control & Instrumentation Engineering, Wonkwang Univ.) ;
  • Ahn, Tae-Chon (Dept. of Control & Instrumentation Engineering, Wonkwang Univ.) ;
  • Oh, Sung-Kwun (Dept. of Control & Instrumentation Engineering, Wonkwang Univ.)
  • 발행 : 1998.07.20

초록

In this paper, we are proposed optimization method of fuzzy model in order to complex and nonlinear system. In the fuzzy modeling, a premise identification is very important to describe the charateristics of a given unknown system. Then, the proposed fuzzy model implements system structure and parameter identification, using the fuzzy inference method and genetic algorithms. Inference method for fuzzy model presented in our paper include the simplified inference and linear inference. Time series data for gas furance and sewage treatment process are used to evaluate the performance of the proposed model. Also, the performance index with weighted value is proposed to achieve a balance between the results of performance for the training and testing data.

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