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Lookup NU author(s): Dr Shady Gadoue, Professor Damian Giaouris, Emeritus Professor John Finch
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This paper presents a novel neural network-based flux observer to solve the low speed problems associated with a model reference adaptive speed estimation scheme which is based on rotor flux. A multilayer feedforward artificial neural network is proposed for rotor flux estimation which is more robust to noise and stator resistance variation and does not have dc-drift problems which are usually associated with these adaptive schemes. A comparison between the performance of the neural network based strategy and conventional scheme is carried out using a validated simulation of an indirect vector controlled induction motor drive working at a low speed. © 2006 IEEE.
Author(s): Gadoue SM, Giaouris D, Finch JW
Publication type: Conference Proceedings (inc. Abstract)
Publication status: Published
Conference Name: 32nd Annual Conference of the IEEE Industrial Electronics Society (IECON 2006)
Year of Conference: 2006
Pages: 1212-1217
ISSN: 1553-572X
Publisher: IEEE
URL: http://dx.doi.org/10.1109/IECON.2006.347284
DOI: 10.1109/IECON.2006.347284
Library holdings: Search Newcastle University Library for this item
ISBN: 1424403901
