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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). 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 with the total least squares (TLS) EXIN neuron. A novel state space-vector representation of the LIM has been deduced, taking into consideration its dynamic end effects. The state equations of the LIM have been rearranged into a matrix form to be solved, in terms of the LIM linear speed, by any least squares technique. The TLS EXIN neuron has been used to compute online, in recursive form, the machine linear speed. A new gain matrix choice of the Luenberger observer, specifically taking into consideration the LIM dynamic end effects, has been proposed, overcoming the limits of the gain matrix choice based on the rotating-induction-machine model. The proposed TLS full-order Luenberger adaptive speed observer has been tested experimentally on an experimental rig. Results have been compared with those achievable with the TLS EXIN MRAS, the classic MRAS, and the sliding-mode MRAS observers.

Item Type: Journal Article
Subjects: T Technology > TA Engineering (General). Civil engineering (General)
T Technology > TJ Mechanical engineering and machinery
Divisions: Faculty of Science, Technology and Environment (FSTE) > School of Engineering and Physics
Depositing User: Fulori Nainoca
Date Deposited: 01 Apr 2015 16:39
Last Modified: 01 Apr 2015 16:39
URI: http://repository.usp.ac.fj/id/eprint/8172

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