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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
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