Proceedings of the KIEE Conference (대한전기학회:학술대회논문집)

The Korean Institute of Electrical Engineers (대한전기학회)
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On-line Modeling for Nonlinear Process Systems using the Adaptive Fuzzy-Neural Network

적응 퍼지-뉴럴 네트워크를 이용한 비선형 공정의 On-line 모델링

  • Park, Chun-Seong (Division of Electrical and Engineering, of Wonkwang University) ;
  • Oh, Sung-Kwun (Division of Electrical and Engineering, of Wonkwang University) ;
  • Kim, Hyun-Ki (Dept. of Electrical Engineering, Suwon University)
  • 박춘성 (원광대학교 전기전자공학부) ;
  • 오성권 (원광대학교 전기전자공학부) ;
  • 김현기 (수원대학교 전기전자정보통신공학부)
  • Published : 1998.11.28
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Abstract

In this paper, we construct the on-line model structure for the nonlinear process systems using the adaptive fuzzy-neural network. Adaptive fuzzy-neural network usually consists of two distinct modifiable structure, with both, the premise and the consequent part. These two parts can be adapted by different optimization methods, which are the hybrid learning procedure combining gradient descent method and least square method. To achieve the on-line model structure, we use the recursive least square method for the consequent parameter identification of nonlinear process. We design the interface between PLC and main computer, and construct the monitoring and control simulator for the nonlinear process. The proposed on-line modeling to real process is carried out to obtain the effective and accurate results.

Keywords