Proceedings of the KIEE Conference (대한전기학회:학술대회논문집)
- 1999.07g
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- Pages.2929-2931
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- 1999
On-line Identification of fuzzy model using HCM algorithm
HCM을 이용한 퍼지 모델의 On-Line 동정
- Park, Ho-Sung (Division of electrical & electronic Engineering, Wonkwang Univ.) ;
- Park, Byoung-Jun (Division of electrical & electronic Engineering, Wonkwang Univ.) ;
- Oh, Sung-Kwun (Division of electrical & electronic Engineering, Wonkwang Univ.)
- Published : 1999.07.19
Abstract
In this paper, an adaptive fuzzy inference and HCM(Hard C-Means) clustering method are used for on-line fuzzy modeling of nonlinear and complex system. Here HCM clustering method is utilized for determining the initial parameter of membership function of fuzzy premise rules and also avoiding overflow phenomenon during the identification of consequence parameters. To obtain the on-line model structure of fuzzy systems. we use the recursive least square method for the consequent parameter identification. And the proposed on-line identification algorithm is carried out and is evaluated for sewage treatment process system.
Keywords