Generalization of the static Preisach model for dynamic hysteresis by a genetic approach

被引:22
作者
Salvini, A [1 ]
Fulginei, FR [1 ]
Pucacco, G [1 ]
机构
[1] Univ Roma Tre, Dipartimento Elettron Applicata, I-146 Rome, Italy
关键词
genetic algorithms (GAs); hysteresis; neural networks (NNs);
D O I
10.1109/TMAG.2003.810538
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
A method able to generalize the static Preisach hysteresis model for dynamic loops under sinusoidal time-varying fields is presented in this paper. The aim is to obtain an equivalent static model for dynamic loops. Then, the Preisach distribution function parameters are updated according to the frequency of the excitation magnetic field. The frequency-dependent parameters have been evaluated by genetic algorithms. Validations based on a comparison of the results of the present approach have been made with a different classical numerical approach modeling dynamic loops.
引用
收藏
页码:1353 / 1356
页数:4
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