Cover Image

Offline artificial neural network rotor flux estimator for induction motor

Rotor flux is an important parameter in field-oriented control of induction motor (IM). It can be obtained through direct physical measurement at the air-gap or indirectly by using estimators. In this paper, the feedforward Artificial Neural Network (ANN) model for rotor flux estimation is proposed...

Full description

Saved in:
Bibliographic Details
Main Authors: Mahsahirun, S. N., Md. Yusof, Z., Idris, N. R. N.
Format: Conference or Workshop Item
Published: 2020
Subjects:
TK Electrical engineering. Electronics Nuclear engineering
Online Access:http://eprints.utm.my/id/eprint/92361/
http://dx.doi.org/10.1109/IICAIET49801.2020.9257845
Tags: Add Tag
No Tags, Be the first to tag this record!
id my.utm.92361
record_format eprints
spelling my.utm.923612021-09-28T07:39:04Z http://eprints.utm.my/id/eprint/92361/ Offline artificial neural network rotor flux estimator for induction motor Mahsahirun, S. N. Md. Yusof, Z. Idris, N. R. N. TK Electrical engineering. Electronics Nuclear engineering Rotor flux is an important parameter in field-oriented control of induction motor (IM). It can be obtained through direct physical measurement at the air-gap or indirectly by using estimators. In this paper, the feedforward Artificial Neural Network (ANN) model for rotor flux estimation is proposed and analyzed. The network is trained using equivalent circuit model data and the Levenberg-Marquardt algorithm. The result shows that the proposed ANN rotor flux estimator is able to perform IM rotor flux estimation with 2.99e-05 MSE. 2020 Conference or Workshop Item PeerReviewed Mahsahirun, S. N. and Md. Yusof, Z. and Idris, N. R. N. (2020) Offline artificial neural network rotor flux estimator for induction motor. In: 2020 IEEE International Conference on Artificial Intelligence in Engineering and Technology, IICAIET 2020, 26 - 27 September 2020, Kota Kinabalu, Sabah. http://dx.doi.org/10.1109/IICAIET49801.2020.9257845
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
topic TK Electrical engineering. Electronics Nuclear engineering
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Mahsahirun, S. N.
Md. Yusof, Z.
Idris, N. R. N.
Offline artificial neural network rotor flux estimator for induction motor
description Rotor flux is an important parameter in field-oriented control of induction motor (IM). It can be obtained through direct physical measurement at the air-gap or indirectly by using estimators. In this paper, the feedforward Artificial Neural Network (ANN) model for rotor flux estimation is proposed and analyzed. The network is trained using equivalent circuit model data and the Levenberg-Marquardt algorithm. The result shows that the proposed ANN rotor flux estimator is able to perform IM rotor flux estimation with 2.99e-05 MSE.
format Conference or Workshop Item
author Mahsahirun, S. N.
Md. Yusof, Z.
Idris, N. R. N.
author_facet Mahsahirun, S. N.
Md. Yusof, Z.
Idris, N. R. N.
author_sort Mahsahirun, S. N.
title Offline artificial neural network rotor flux estimator for induction motor
title_short Offline artificial neural network rotor flux estimator for induction motor
title_full Offline artificial neural network rotor flux estimator for induction motor
title_fullStr Offline artificial neural network rotor flux estimator for induction motor
title_full_unstemmed Offline artificial neural network rotor flux estimator for induction motor
title_sort offline artificial neural network rotor flux estimator for induction motor
publishDate 2020
url http://eprints.utm.my/id/eprint/92361/
http://dx.doi.org/10.1109/IICAIET49801.2020.9257845
_version_ 1712285083611693056
score 13.250246

Similar Items