제어규칙 퍼지모델링과 폐수처리 시스템 응용 = Control Rules-Based Fuzzy Modeling and its Application to Wastewater treatment System

다국어 초록 (Multilingual Abstract)

A design method of rule-baaed fuzzy modeling is proposed for the model identification of nonlinear systems. The Proposed rule-based fuzzy modeling implements system structure and parameter identification in the efficient form of "IF…", THEN…", using the intelligent theories of optimization theory. Linguistic fuzzy implication rules and neural networks(NNs). The method for rule-based fuzzy modeling based on linear fuzzy inference is presented in this paper. The structure identification of fuzzy implication rules is carried out utilizing fuzzy c-means clustering in order to avoid the iterative fuzzy Partition in the' conventional identification and fuzzy-neural networks (FNNs) are used to identify parameters of premise and consequence part of fuzzy implication rules. To obtain the optimal fuzzy rules, the learning ratio and momentum coefficients of FNNs are tuned automatically utilizing the modified complex method. Time series data for gas furnace are used to evaluate the performance of the proposed rule-based fuzzy modeling. Comparison shows that the proposed method can produce the fuzzy model with higher accuracy than previously achieved in other work.