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
کلیدواژهها
نویسندگان
Behnam Mehrkian
Department of Civil Engineering, University of Guilan, Rasht, Guilan
آرش بهار
Behnam Mehrkian Department of Civil Engineering, University of Guilan, Rasht, GuilanAli Chaibakhsh Department of Mechanical Engineering, University of Guilan, Rasht, Guilan
Ali Chaibakhsh
Department of Mechanical Engineering, University of Guilan, Rasht, Guilan
شیوه ارجاع
Mehrkian, Behnam and Bahar, Arash and Chaibakhsh, Ali,1391,GA-optimized neuro-fuzzy approach for nonlinear system modeling,9th International Congress on Civil Engineering,Isfahan
ارائهشده در
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