Study of the Flux Observer and its Optimizing Strategy for Induction Motor based on Extended Kalman Filter

被引：0
|
作者：
Zhang Yongjun [1 ]
Jing, Wang [1 ]
He, Chuan [2 ]
机构：
[1] Univ Sci & Technol, Inst Informat Engn, Beijing 100083, Peoples R China
[2] Texas A&M Univ, Inst Sci Computat, College Stn, TX 77843 USA
来源：
ICEMS 2008: PROCEEDINGS OF THE 11TH INTERNATIONAL CONFERENCE ON ELECTRICAL MACHINES AND SYSTEMS, VOLS 1- 8 | 2008年
关键词：
D O I：
暂无
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 flux linkage estimation method for induction motor based on Extended Kalman Filter theory (EKF) is presented in this paper. In order to improve the accuracy of filtering, Genetic Algorithm (GA) is introduced to optimize the noise matrix, and also filtering parameters in EKF. Simulation results show that the flux observer with optimized filtering parameter has better estimation accuracy and dynamic performance at tow speed.
引用
收藏
页码：4028 / +
页数：2
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