Title :
Speed estimation of induction motor 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 proposes two techniques for speed estimation of induction motors using artificial neural networks. The techniques are based on speed expressions obtained from the induction motor dynamic equations. Two of the equations obtained have singularities, and hence direct speed estimation from these is not possible. The paper proposes a scheme using two ANNs to recover the speed from these two equations. However, it is possible to combine these two equations in a way that removes the singularities. Another method, based on this equation, is presented for obtaining the speed directly from the output of an ANN. These methods are general and easily implementable using commercially available ANN devices
Keywords :
electric machine analysis computing; induction motors; machine control; neural nets; parameter estimation; velocity control; artificial neural networks; induction motor; induction motor dynamic equations; singularities; speed control; speed estimation; Artificial neural networks; DC motors; Induction motor drives; Induction motors; Machine vector control; Motor drives; Nonlinear equations; Rotors; Torque control; Velocity control;
Conference_Titel :
Industrial Electronics, Control, and Instrumentation, 1996., Proceedings of the 1996 IEEE IECON 22nd International Conference on
Conference_Location :
Taipei
Print_ISBN :
0-7803-2775-6
DOI :
10.1109/IECON.1996.565994