제어로봇시스템학회:학술대회논문집
- 1993.10a
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- Pages.200-205
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- 1993
Fuzzy identification by means of fuzzy inference method
퍼지추론 방법에 의한 퍼지동정
Abstract
A design method of rule-based fuzzy modeling is presented for the model identification of complex and nonlinear systems. Three kinds of method for fuzzy modeling presented in this paper include simplified inference (type 1), linear inference (type 2), and modified linear inference (type 3). The fuzzy c-means clustering and modified complex methods are used in order to identify the preise structure and parameter of fuzzy implication rules, respectively and the least square method is utilized for the identification of optimal consequence parameters. Time series data for gas funace and sewage treatment processes are used to evaluate the performances of the proposed rule-based fuzzy modeling.
Keywords