http://www.cnr.it/ontology/cnr/individuo/prodotto/ID194509
MRAS Speed Observer for High-Performance Linear Induction Motor Drives Based on Linear Neural Networks (Articolo in rivista)
- Type
- Label
- MRAS Speed Observer for High-Performance Linear Induction Motor Drives Based on Linear Neural Networks (Articolo in rivista) (literal)
- Anno
- 2013-01-01T00:00:00+01:00 (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
- 10.1109/TPEL.2012.2200506 (literal)
- Alternative label
Accetta Angelo, Cirrincione Maurizio, Pucci Marcello, Gianpaolo Vitale. (2013)
MRAS Speed Observer for High-Performance Linear Induction Motor Drives Based on Linear Neural Networks
in IEEE transactions on power electronics
(literal)
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- Accetta Angelo, Cirrincione Maurizio, Pucci Marcello, Gianpaolo Vitale. (literal)
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- http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6203599 (literal)
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- Accetta Angelo: CNR - ISSIA UOS di Palermo
Cirrincione Maurizio: Universit´e Technologique de Belfort Montbeliard,
90010 Belfort, France (e-mail: m.cirrincione@ieee.org). (literal)
- Titolo
- MRAS Speed Observer for High-Performance Linear Induction Motor Drives Based on Linear Neural Networks (literal)
- 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- (literal)
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