Title :
Induction motor speed estimation using artificial neural networks
Author :
Mehrotra, Prashant ; Quaicoe, John E. ; Venkatesan, R.
Author_Institution :
Fac. of Eng. & Appl. Sci., Memorial Univ. of Newfoundland, St. John´´s, Nfld., Canada
Abstract :
This paper derives two functional relationships between the stator quantities and speed from the induction motor dynamic equations. As singularities are present in these relationships, direct estimation of speed using artificial neural networks (ANNs) with these stator inputs is not possible. The paper proposes a scheme which employs two ANNs for this purpose. The outputs of the two ANNs are further processed to obtain the induction motor speed. The speed recovery scheme does not depend upon any particular control strategy
Keywords :
electric machine analysis computing; induction motor drives; machine theory; neural nets; parameter estimation; stators; artificial neural networks; dynamic equations; induction motor drives; speed estimation; speed recovery scheme; stator; Artificial neural networks; Backpropagation algorithms; DC motors; Equations; Induction motor drives; Induction motors; Machine vector control; Motor drives; Neural networks; Stators;
Conference_Titel :
Electrical and Computer Engineering, 1996. Canadian Conference on
Conference_Location :
Calgary, Alta.
Print_ISBN :
0-7803-3143-5
DOI :
10.1109/CCECE.1996.548226