Offline artificial neural network rotor flux estimator for induction motor

Siti Nursyuhada, Mahsahirun and Zulkifli, Md Yusof and Nik Rumzi, Nik Idris (2020) Offline artificial neural network rotor flux estimator for induction motor. In: IEEE International Conference on Artificial Intelligence in Engineering and Technology, IICAIET 2020. 2020 IEEE International Conference on Artificial Intelligence in Engineering and Technology, IICAIET 2020 , 26 - 27 September 2020 , Kota Kinabalu, Sabah. pp. 1-6. (9257845). ISBN 978-172816946-0 (Published)

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Abstract

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.

Item Type:	Conference or Workshop Item (Lecture)
Additional Information:	Indexed by Scopus
Uncontrolled Keywords:	Artificial neural network estimator; Induction motor rotor flux estimator; Levenberg-Marquardt algorithm
Subjects:	T Technology > T Technology (General) T Technology > TA Engineering (General). Civil engineering (General) T Technology > TJ Mechanical engineering and machinery T Technology > TK Electrical engineering. Electronics Nuclear engineering T Technology > TS Manufactures
Faculty/Division:	Institute of Postgraduate Studies Faculty of Manufacturing and Mechatronic Engineering Technology
Depositing User:	Mr Muhamad Firdaus Janih@Jaini
Date Deposited:	30 Oct 2024 04:45
Last Modified:	30 Oct 2024 04:45
URI:	http://umpir.ump.edu.my/id/eprint/42436
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