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...
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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 |
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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 |
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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. |
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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 |
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2020 |
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http://eprints.utm.my/id/eprint/92361/ http://dx.doi.org/10.1109/IICAIET49801.2020.9257845 |
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1712285083611693056 |
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13.211869 |