MRAS Speed Observer for High-Performance Linear Induction Motor Drives Based on Linear Neural Network

Cirrincione, Maurizio and Accetta, A. and Pucci , Marcello and Vitale, Gianpaolo (2013) MRAS Speed Observer for High-Performance Linear Induction Motor Drives Based on Linear Neural Network. IEEE Transactions on Power Electronics, 28 (1). pp. 123-134. ISSN 0885-8993

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Abstract

This paper proposes a neural network (NN) model reference adaptive system (MRAS) speed observer suited for linear induction motor (LIM) drives. The voltage and current flux models of the LIM in the stationary reference frame, taking into consideration the end effects, have been first deduced. Then, the induced part equations have been discretized and rearranged so as to be represented by a linear NN (ADALINE). On this basis, the transport layer security EXIN neuron has been used to compute online, in recursive form, the machine linear speed. The proposed NN MRAS observer has been tested experimentally on suitably developed test set-up. Its performance has been further compared to the classic MRAS and the sliding-mode MRAS speed observers developed for the rotating machines.

Item Type:	Journal Article
Uncontrolled Keywords:	Mathematical model, Observers, Inductors, Adaptation models, Equations, Adaptive filters, Artificial neural networks
Subjects:	T Technology > T Technology (General)
Divisions:	Faculty of Science, Technology and Environment (FSTE) > School of Engineering and Physics
Depositing User:	USP RSC Assistant
Date Deposited:	05 Oct 2017 04:20
Last Modified:	21 May 2019 21:14
URI:	https://repository.usp.ac.fj/id/eprint/10181

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