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Speed observation of linear induction motor based on extended Kalman filter

Authors :
HOU Xinguo
TU Xuan
ZHAO Jinghong
MA Yuanzheng
LUO Xiangyu
Source :
电力工程技术, Vol 43, Iss 3, Pp 226-233 (2024)
Publication Year :
2024
Publisher :
Editorial Department of Electric Power Engineering Technology, 2024.

Abstract

In order to solve the problem of lacking velocity feedback information in the velocity closed-loop control system for linear induction motors (LIM) after cancelling the velocity sensor, a velocity observer based on the extended Kalman filtering algorithm has been implemented, considering the end edge effect of LIM. Firstly, based on the mathematical model of three-phase linear induction motor considering edge effect, an extended Kalman filter observer with appropriate gain and covariance update matrix is derived. Based on the vector control system of LIM, the speed parameters identified by the observer are fed back to the speed closed-loop system. Then, the vector control system model of linear induction motor with speed observer is built in Simulink, and the identification speed of observer is compared with the actual speed of motor. Finally, the results show that the closed-loop control using the identification speed can ensure the stable operation of the system. Under three kinds of loads, the error between the predicted speed and the actual speed of the observer is form 0.51% to 2.34%. The various dynamic performance of the system reveals that the LIM vector control system based on the extended Kalman filter observer increases prediction velocity error and decreases thrust error with increasing load. However, the magnetic flux amplitude error slightly increases. Therefore, considering the end-edge effect, the observer based on the extended Kalman filter can replace the velocity sensor to achieve three-phase LIM control under both unloaded and loaded conditions.

Details

Language :
Chinese
ISSN :
20963203
Volume :
43
Issue :
3
Database :
Directory of Open Access Journals
Journal :
电力工程技术
Publication Type :
Academic Journal
Accession number :
edsdoj.2217603bbe72425484a97424ff3c1f06
Document Type :
article
Full Text :
https://doi.org/10.12158/j.2096-3203.2024.03.024