Non-parametric induction motor rotor flux estimator based on feed-forward neural network

Siti Nursyuhada, Mahsahirun and Nik Rumzi, Nik Idris and Zulkifli, Md. Yusof and Sutikno, Tole (2022) Non-parametric induction motor rotor flux estimator based on feed-forward neural network. International Journal of Power Electronics and Drive Systems, 13 (2). pp. 1229-1237. ISSN 2088-8694. (Published)

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Abstract

The conventional induction motor rotor flux observer based on current model and voltage model are sensitive to parameter uncertainties. In this paper, a non-parametric induction motor rotor flux estimator based on feed-forward neural network is proposed. This estimator is operating without motor parameters and therefore it is independent from parameter uncertainties. The model is trained using Levenberg-Marquardt algorithm offline. All the data collection, training and testing process are fully performed in MATLAB/Simulink environment. A forced iteration of 1,000-epochs is imposed in the training process. There are overall 603,968 datasets are used in this modeling process. This four-input two-output neural network model is capable of providing rotor flux estimation for field-oriented control systems with 3.41e-9 mse and elapsed 28 minutes 49 seconds training time consumption. This proposed model is tested with reference speed step response and parameters uncertainties. The result indicates that the proposed estimator improves voltage model and current model rotor flux observers for parameters uncertainties.

Item Type: Article
Additional Information: Indexed by Scopus
Uncontrolled Keywords: Field-oriented control; Induction motor; Levenberg-Marquardt algorithm; Neural networks application; Rotor flux estimator
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
Faculty of Mechanical and Automotive Engineering Technology
Depositing User: Mr Muhamad Firdaus Janih@Jaini
Date Deposited: 07 Jan 2025 03:48
Last Modified: 07 Jan 2025 03:48
URI: http://umpir.ump.edu.my/id/eprint/42664
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