GA-optimized neuro-fuzzy approach for nonlinear system modeling
محل انتشار: نهمین کنگره بین الملی مهندسی عمران
سال انتشار: 1391
نوع سند: مقاله کنفرانسی
زبان: انگلیسی
مشاهده: 1,119
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شناسه ملی سند علمی:
ICCE09_1119
تاریخ نمایه سازی: 7 مهر 1391
چکیده مقاله:
In order to characterize the behavior of nonlinear dynamic systems many different approaches have been proposed in recent years. One of the best black-box models employed to deal with system nonlinearities is the combination of artificial neural network (ANN) and fuzzy logic system (FLS), which is known as neuro-fuzzy system. However, the gradient-based nature of this combination causes some deficiencies. Therefore, in this paper, an optimization approach which utilizes genetic algorithm (GA) as a derivativefreeoptimizer is proposed for both designing the structure of neuro-fuzzy model and assessing the model parameters. The whole proposed approach is applied to approximate: first, a nonlinear plant; next, nonlinear dynamic behavior of magneto-rheological (MR) damper, which is widely used in semi-active control of structures and its identification is significantly difficult due to inherent hysteretic and highly nonlinear behavior of the device. Comparisons between the responses of the models and the reference data show high accuracy and feasibility of the proposed approach.
کلیدواژه ها:
نویسندگان
Behnam Mehrkian
Department of Civil Engineering, University of Guilan, Rasht, Guilan
Ali Chaibakhsh
Department of Mechanical Engineering, University of Guilan, Rasht, Guilan