Modeling dynamic hysteresis for giant magnetostrictive actuator using hybrid genetic algorithm

被引：25

作者：

Cao, SY ^{[1
]}

Wang, BW ^{[1
]}

Zheng, JJ ^{[1
]}

Huang, WM ^{[1
]}

Sun, Y ^{[1
]}

Yang, QX ^{[1
]}

机构：

[1] Hebei Univ Technol, Province Minist Joint Key Lab Electromagnet Field, Tianjin 300130, Peoples R China

来源：

IEEE TRANSACTIONS ON MAGNETICS | 2006年 / 42卷 / 04期

基金：

中国国家自然科学基金;

关键词：

dynamic hysteresis model; hybrid genetic algorithm (HGA); Jiles-Atherton model; magnetostrictive actuator (MA);

D O I：

10.1109/TMAG.2006.871465

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：

This paper establishes a simple and novel dynamic hysteresis model for giant magnetostrictive actuator by considering the eddy current loss, anomalous loss and structural dynamic mechanical behavior of the actuator. To obtain parameters of the model, a hybrid genetic algorithm is proposed. Comparisons between the experimental and calculated results show the validity and practicability of the model.

引用

页码：911 / 914

页数：4

共 12 条

[1] A subspace, interior, and conjugate gradient method for large-scale bound-constrained minimization problems [J].