An MRAS Sensorless Technique based on the MCA EXIN + Neuron for High Performance Induction Motor Drives (Articolo in rivista)

Type
Label
  • An MRAS Sensorless Technique based on the MCA EXIN + Neuron for High Performance Induction Motor Drives (Articolo in rivista) (literal)
Anno
  • 2005-01-01T00:00:00+01:00 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
  • 10.7305 (literal)
Alternative label
  • M. Cirrincione, M. Pucci, G. Cirrincione, G. Capolino (2005)
    An MRAS Sensorless Technique based on the MCA EXIN + Neuron for High Performance Induction Motor Drives
    in Automatika (Online)
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • M. Cirrincione, M. Pucci, G. Cirrincione, G. Capolino (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#url
  • https://automatika.korema.hr/index.php/automatika (literal)
Rivista
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
  • ISSIA-CNR, uos di Palermo University of Belfort, France University of Amiens-France (literal)
Titolo
  • An MRAS Sensorless Technique based on the MCA EXIN + Neuron for High Performance Induction Motor Drives (literal)
Abstract
  • This paper proposes a new sensorless technique for induction motor drives based on a hybrid MRAS-neural technique, which improves a previously developed neural MRAS based sensorless method. In this paper the open- -loop integration in the reference model is performed by an adaptive neural integrator, enhanced here by means of a speed-varying filter transfer function. The adaptive model is based on a more accurate discrete current model based on the modified Euler integration, with a resulting more stable behaviour in the field weakening region. The adaptive model is further trained on-line by a generalized least squares technique, the MCA EXIN + neu- ron, in which a parameterized learning algorithm is used. As a consequence, the speed estimation presents an im- proved convergence with higher accuracy and shorter settling time, because of the better transient behaviour of the neuron. A test bench has been set up to verify the methodology experimentally and the results prove its goodness at very low speeds (below 4 rad/s) and in zero-speed operation. (literal)
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