DocumentCode :
303174
Title :
Development of an artificial neural network based induction motor speed estimator
Author :
Mehrotra, Prashant ; Quaicoe, John E. ; Venkatesan, R.
Author_Institution :
Fac. of Eng. & Appl. Sci., Memorial Univ. of Newfoundland, St. John´´s, Nfld., Canada
Volume :
1
fYear :
1996
fDate :
23-27 Jun 1996
Firstpage :
682
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. This paper proposes a scheme which employs two ANNs to recover motor speed. An added benefit of this scheme is that it can be used quite easily in the presence of an inverter without the need for a smoothing filter for the feedback quantities. This method is general, robust and implementable using commercially available ANN devices
Keywords :
control system analysis; feedback; induction motors; machine control; machine theory; neurocontrollers; parameter estimation; robust control; stators; velocity control; artificial neural network; control simulation; feedback quantities; functional relationships; induction motor speed estimator; inverter; motor dynamic equations; motor speed control; motor speed recovery; robustness; singularities; stator quantities; Artificial neural networks; DC motors; Induction motor drives; Induction motors; Machine vector control; Robustness; Rotors; Servomechanisms; Stators; Velocity control;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Power Electronics Specialists Conference, 1996. PESC '96 Record., 27th Annual IEEE
Conference_Location :
Baveno
ISSN :
0275-9306
Print_ISBN :
0-7803-3500-7
Type :
conf
DOI :
10.1109/PESC.1996.548655
Filename :
548655
Link To Document :
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