DocumentCode
553778
Title
Neural network aided unscented Kalman filter for sensorless control of PMSM
Author
Talla, Jakub ; Peroutka, Zdenek
Author_Institution
Regional Innovation Centre for Electr. Eng., Univ. of West Bohemia, Pilsen, Czech Republic
fYear
2011
fDate
Aug. 30 2011-Sept. 1 2011
Firstpage
1
Lastpage
9
Abstract
This paper introduces neural network aided unscented Kalman filter (NNUKF) for sensorless control of ac motor drives. Unscented Kalman filter (UKF) is completed by on-line trained neural network which compensates unmodeled dynamics and uncertainties of a drive model. This technique significantly improves behaviour of estimator in critical operating states, especially in low speeds.
Keywords
Kalman filters; neurocontrollers; permanent magnet motors; sensorless machine control; synchronous motor drives; ac motor drives; critical operating states; neural network aided unscented Kalman filter; permanent magnet synchronous motor; sensorless control; Adaptation models; Artificial neural networks; Estimation; Kalman filters; Mathematical model; Rotors; Sensorless control; Estimation technique; Neural network; Permanent magnet motor; Sensorless control;
fLanguage
English
Publisher
ieee
Conference_Titel
Power Electronics and Applications (EPE 2011), Proceedings of the 2011-14th European Conference on
Conference_Location
Birmingham
Print_ISBN
978-1-61284-167-0
Electronic_ISBN
978-90-75815-15-3
Type
conf
Filename
6020637
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