Neural sensorless control of linear induction motors by a full - order Luenberger observer considering the end - effects

Accetta, A. and Cirrincione, Maurizio and Pucci, M. and Vitale, G. (2014) Neural sensorless control of linear induction motors by a full - order Luenberger observer considering the end - effects. IEEE Transactions on Industry Applications, 50 (3). pp. 1891-1904. ISSN 0093-9994

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Abstract

This paper proposes a neural based full-order Luenberger Adaptive speed observer for sensorless linear induction motor (LIM) drives, where the linear speed is estimated on the basis of the linear neural network: TLS EXIN neuron. With this reference, a novel state space-vector representation of the LIM has been deduced, taking into consideration the so-called end effects. Starting from this standpoint, the state equation of the LIM has been discretized and rearranged in a matrix form to be solved by a least-square technique. The TLS EXIN neuron has been used to compute on-line, in recursive form, the machine linear speed since it is the only neural network able to solve on-line in a recursive form a total least-squares problem. The proposed TLS full-order Luenberger Adaptive speed observer has been tested experimentally on suitably developed test setup.

Item Type:	Journal Article
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions:	Faculty of Science, Technology and Environment (FSTE) > School of Engineering and Physics
Depositing User:	Ms Shalni Sanjana
Date Deposited:	10 Dec 2014 04:03
Last Modified:	03 May 2016 22:47
URI:	https://repository.usp.ac.fj/id/eprint/7855

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