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
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;
Conference_Titel :
Power Conversion Conference, 1993. Yokohama 1993., Conference Record of the
Conference_Location :
Yokohama, Japan
Print_ISBN :
0-7803-0471-3
DOI :
10.1109/PCCON.1993.264173