Modeling of SRM Based on XS-LSSVR Optimized by GDS

被引：15

作者：

Hou Likun ^{[1
,2
]}

Yang Qingxin ^{[3
]}

An Jinlong ^{[1
]}

机构：

[1] Hebei Univ Technol, Prov Minist Joint Key Lab Electromagnet Field & E, Tianjin 300131, Peoples R China

[2] Tianjin Univ Commerce, Tianjin, Peoples R China

[3] Tianjin Polytech Univ, Tianjin 300160, Peoples R China

来源：

IEEE TRANSACTIONS ON APPLIED SUPERCONDUCTIVITY | 2010年 / 20卷 / 03期

关键词：

Grid-diamond searching; least square support vector machine regression; modeling; switched reluctance motor;

D O I：

10.1109/TASC.2010.2043518

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：

Considering nonlinear magnetization characteristic of switched reluctance motor (SRM), this paper describes a nonlinear model of SRM based on an improved least square support vector machine regression (LSSVR) algorithm optimized by grid-diamond searching (GDS) method. The experimental results show that the GDS method can choose proper parameters of LSSVR while providing better simulation result. Modeling with the optimization parameter, the forecasted data of the model are compared with the experimental data on a four-phase, 8/6 SRM. It is shown that XS-LSSVR optimized by GDS is effectiveness method and performs better forecast accuracy and successful modeling of SRM.

引用

页码：1102 / 1105

页数：4

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