Proceedings of the KIEE Conference (대한전기학회:학술대회논문집)

The Korean Institute of Electrical Engineers (대한전기학회)
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Fuzzy Modeling of Truck-Trailer Backing Problem Using DNA Coding-Based Hybrid Algorithm

DNA 코딩 기반의 하이브리드 알고리즘을 이용한 Truck-Trailer Backing Problem의 퍼지 모델링

  • Kim, Jang-Hyun (Dept. of Electrical & Computer Engineering, Yonsei Univ.) ;
  • Joo, Young-Hoon (School of Electronics & Information Eng., Kunsan Univ.) ;
  • Park, Jin-Bae (Dept. of Electrical & Computer Engineering, Yonsei Univ.)
  • 김장현 (연세대 전기.컴퓨터공학과) ;
  • 주영훈 (군산대 공대 전자정보공학부) ;
  • 박진배 (연세대 전기.컴퓨터공학과)
  • Published : 2000.07.17
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Abstract

In the construction of successful fuzzy models and/or controllers for nonlinear systems, identification of a good fuzzy Neural inference system is an important yet difficult problem, which is traditionally accomplished by trial and error process. In this paper, we propose a systematic identification procedure for complex multi-input single- output nonlinear systems with DNA coding method.DNA coding method is optimization algorithm based on biological DNA as are conventional genetic algothms (GAs). We also propose a new coding method for applying the DNA coding method to the identification of fuzzy Neural models. To acquire optimal TS fuzzy model with higher accuracy and economical size, we use the DNA coding method to optimize the parameters and the number of fuzzy inference system.

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