Identification of a Nonlinear System by Determining of Fuzzy Rules
سال انتشار: 1395
نوع سند: مقاله ژورنالی
زبان: انگلیسی
مشاهده: 313
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شناسه ملی سند علمی:
JR_JIST-4-4_003
تاریخ نمایه سازی: 7 شهریور 1396
چکیده مقاله:
In this article the hybrid optimization algorithm of differential evolution and particle swarm is introduced for designing the fuzzy rule base of a fuzzy controller. For a specific number of rules, a hybrid algorithm for optimizing allopen parameters was used to reach maximum accuracy in training. The considered hybrid computational approach includes: opposition-based differential evolution algorithm and particle swarm optimization algorithm. To train a fuzzysystem hich is employed for identification of a nonlinear system, the results show that the proposed hybrid algorithm approach demonstrates a better identification accuracy compared to other educational approaches in identification of thenonlinear system model. The example used in this article is the Mackey-Glass Chaotic System on which the proposed method is finally applied.
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نویسندگان
Hodjatollah Hamidi
Department of Industrial Engineering, K. N. Toosi University of Technology, Tehran, Iran
Atefeh Daraei
Department of Industrial Engineering, K. N. Toosi University of Technology, Tehran, Iran