Symbiotic Organism Search of a NonLinear Kalman Filter for Induction Motors Sensor-less Control

被引：0
|
作者：
Ghodsinya, S. R. Movahhed [1 ]
Azimirad, E. [1 ]
Noorabadi, M. [1 ]
机构：
[1] Univ Torbat Heydarieh, Fac Engn, Elect Engn Dept, Torbat Heydarieh, Iran
来源：
2020 11TH POWER ELECTRONICS, DRIVE SYSTEMS, AND TECHNOLOGIES CONFERENCE (PEDSTC) | 2020年
关键词：
Field Oriented Control (FOC); Extended Kalman Filter (EKF); Induction Motor; Symbiotic Organism Search;
D O I：
暂无
中图分类号：
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号：
0807 ; 0820 ;
摘要：
In this paper a new strategy presents for achieving a high performance estimation for controlling the sensorless induction Motors presents. The suggested technique uses the Symbiotic Organism Search Optimization (SOS) algorithm to tune the Extended Kalman Filter observer through evaluating noise matrix (R) and resolving the optimal covariance matrix (Q) values. The overall idea is to construct optimized Extended Kalman Filter observer with the basic one. Results of the simulation verified the efficacy in terms of accuracy and adaptive performance of the proposed strategy.
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页数：5
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