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A Study on On-line modeling of Fuzzy System via Extended Kalman Filter  

김은태 (연세대학교 전기전자공학부)
Publication Information
Journal of the Institute of Electronics Engineers of Korea CI / v.40, no.5, 2003 , pp. 250-258 More about this Journal
Abstract
In this paper, an explanation regarding on-line identification of a fuzzy system is presented. The fuzzy system to be identified is assumed to be in the type of singleton consequent parts and be represented by a linear combination of fuzzy basis functions. For on-line identification, squared-cosine membership function is introduced to reduce the number of parameters to be identified and make the system consistent and differentiable. Then the parameters of the fuzzy system are identified on-line by the gradient search method and Extended Kalman Filter. Finally, a computer simulation is peformed to illustrate the validity of the suggested algorithms.
Keywords
확장칼만필터;온라인 퍼지 모델링;타입 2;
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