Identification of a Nonlinear System by Determining of Fuzzy Rules
عنوان مقاله: Identification of a Nonlinear System by Determining of Fuzzy Rules
شناسه ملی مقاله: JR_JIST-4-4_003
منتشر شده در شماره 4 دوره 4 فصل Autumn در سال 1395
شناسه ملی مقاله: JR_JIST-4-4_003
منتشر شده در شماره 4 دوره 4 فصل Autumn در سال 1395
مشخصات نویسندگان مقاله:
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
خلاصه مقاله:
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
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.
کلمات کلیدی: System Identification; Combined Training; Fuzzy Rules; Database Design
صفحه اختصاصی مقاله و دریافت فایل کامل: https://civilica.com/doc/630920/