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Title: Tuning the stator resistance of induction motors using artificial neural network

Abstract

Tuning the stator resistance of induction motors is very important, especially when it is used to implement direct torque control (DTC) in which the stator resistance is a main parameter. In this paper, an artificial network (ANN) is used to accomplish tuning of the stator resistance of an induction motor. The parallel recursive prediction error and backpropagation training algorithms were used in training the neural network for the simulation and experimental results, respectively. The neural network used to tune the stator resistance was trained on-line, making the DTC strategy more robust and accurate. Simulation results are presented for three different neural-network configurations showing the efficiency of the tuning process. Experimental results were obtained for the one of the three neural-network configuration. Both simulation and experimental results showed that the ANN have tuned the stator resistance in the controller to track actual resistance of the machine.

Authors:
; ;  [1]
  1. Univ. of Akron, OH (United States). Dept. of Electrical Engineering
Publication Date:
OSTI Identifier:
538087
Resource Type:
Journal Article
Journal Name:
IEEE Transactions on Power Electronics
Additional Journal Information:
Journal Volume: 12; Journal Issue: 5; Other Information: PBD: Sep 1997
Country of Publication:
United States
Language:
English
Subject:
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION; NEURAL NETWORKS; ELECTRIC MOTORS; ARTIFICIAL INTELLIGENCE; POWER SUPPLIES; STATORS; PERFORMANCE; ELECTRIC CONDUCTIVITY

Citation Formats

Cabrera, L A, Elbuluk, M E, and Husain, I. Tuning the stator resistance of induction motors using artificial neural network. United States: N. p., 1997. Web. doi:10.1109/63.622995.
Cabrera, L A, Elbuluk, M E, & Husain, I. Tuning the stator resistance of induction motors using artificial neural network. United States. https://doi.org/10.1109/63.622995
Cabrera, L A, Elbuluk, M E, and Husain, I. 1997. "Tuning the stator resistance of induction motors using artificial neural network". United States. https://doi.org/10.1109/63.622995.
@article{osti_538087,
title = {Tuning the stator resistance of induction motors using artificial neural network},
author = {Cabrera, L A and Elbuluk, M E and Husain, I},
abstractNote = {Tuning the stator resistance of induction motors is very important, especially when it is used to implement direct torque control (DTC) in which the stator resistance is a main parameter. In this paper, an artificial network (ANN) is used to accomplish tuning of the stator resistance of an induction motor. The parallel recursive prediction error and backpropagation training algorithms were used in training the neural network for the simulation and experimental results, respectively. The neural network used to tune the stator resistance was trained on-line, making the DTC strategy more robust and accurate. Simulation results are presented for three different neural-network configurations showing the efficiency of the tuning process. Experimental results were obtained for the one of the three neural-network configuration. Both simulation and experimental results showed that the ANN have tuned the stator resistance in the controller to track actual resistance of the machine.},
doi = {10.1109/63.622995},
url = {https://www.osti.gov/biblio/538087}, journal = {IEEE Transactions on Power Electronics},
number = 5,
volume = 12,
place = {United States},
year = {Mon Sep 01 00:00:00 EDT 1997},
month = {Mon Sep 01 00:00:00 EDT 1997}
}