DocumentCode
3506623
Title
Identification of induction motor speed using neural networks
Author
Ben-Brahim, Lazhar ; Kurosawa, Ryoichi
Author_Institution
Heavy Apapratus Eng. Lab., Toshiba Corp., Tokyo, Japan
fYear
1993
fDate
19-21 April 1993
Firstpage
689
Lastpage
694
Abstract
A newly developed approach to identify the mechanical speed of an induction motor based on the neural networks technique is described. The backpropagation neural network technique is used to provide a real-time adaptive estimation of the motor speed. The error between the desired state variable and the actual one is backpropagated to adjust the rotor speed, so that the actual state variable will coincide with the desired one. The backpropagation mechanism is easy to derive and the estimated speed tracks precisely the actual motor speed. A theoretical analysis as well as simulation results to verify the effectiveness of the new method are described in this paper.<>
Keywords
backpropagation; control system analysis; digital control; induction motors; machine control; machine theory; neural nets; parameter estimation; real-time systems; rotors; velocity control; backpropagation; control system analysis; digital control; induction motor; machine control; machine theory; mechanical speed; neural networks; parameter estimation; real-time; rotor; simulation; velocity control; Adaptive estimation; Analytical models; Feedforward neural networks; Induction motors; Multi-layer neural network; Neural networks; Process control; Rotors; State estimation; Stators;
fLanguage
English
Publisher
ieee
Conference_Titel
Power Conversion Conference, 1993. Yokohama 1993., Conference Record of the
Conference_Location
Yokohama, Japan
Print_ISBN
0-7803-0471-3
Type
conf
DOI
10.1109/PCCON.1993.264173
Filename
264173
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