Modeling and simulation of position estimation of switched reluctance motor with artificial neural networks
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Dosyalar
Tarih
2009
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
In the present study, position estimation of switched reluctance motor (SRM) has been achieved on the basis of the artificial neural networks (ANNs). The ANNs can estimate the rotor position without using an extra rotor position sensor by measuring the phase flux linkages and phase currents. Flux linkage-phase current-rotor position data set and supervised back propagation learning algorithm are used in training of the ANN based position estimator. A 4-phase SRM have been used to verify the accuracy and feasibility of the proposed position estimator. Simulation results show that the proposed position estimator gives precise and accurate position estimations for both under the low and high level reference speeds of the SRM.
Açıklama
Anahtar Kelimeler
Artificial Neural Networks, Modeling And Simulation, Position Observer, Switched Reluctance Motor
Kaynak
World Academy of Science, Engineering and Technology
WoS Q Değeri
Scopus Q Değeri
N/A
Cilt
57
