DocumentCode
483083
Title
Study of the flux observer and its optimizing strategy for induction motor based on Extended Kalman Filter
Author
Yongjun, Zhang ; Jing, Wang ; He, Chuan
Author_Institution
Instn. of Inf. Eng., Univ. of Sci. & Technol., Beijing
fYear
2008
fDate
17-20 Oct. 2008
Firstpage
4028
Lastpage
4032
Abstract
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 low speed.
Keywords
Kalman filters; genetic algorithms; induction motors; machine control; matrix algebra; power filters; torque control; direct torque control; extended Kalman filter; flux linkage estimation method; flux observer; genetic algorithm; induction motor control; noise matrix optimisation; Couplings; Filtering; Genetic algorithms; Induction motors; Low pass filters; Nonlinear equations; State estimation; Stators; Uncertainty; Voltage;
fLanguage
English
Publisher
ieee
Conference_Titel
Electrical Machines and Systems, 2008. ICEMS 2008. International Conference on
Conference_Location
Wuhan
Print_ISBN
978-1-4244-3826-6
Electronic_ISBN
978-7-5062-9221-4
Type
conf
Filename
4771487
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