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An MRAS Sensorless Technique Based on the MCA EXIN + Neuron for High Performance Induction Motor Drives

Maurizio Cirrincione
Marcello Pucci
Giansalvo Cirrincione
Gérard-André Capolino


Puni tekst: engleski pdf 714 Kb

str. 59-72

preuzimanja: 1.455

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Sažetak

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 + neuron, in which a parameterized learning algorithm is used. As a consequence, the speed estimation presents an improved 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.

Ključne riječi

induction motor drives; sensorless control; model reference adaptive systems; neural networks

Hrčak ID:

6842

URI

https://hrcak.srce.hr/6842

Datum izdavanja:

21.12.2005.

Podaci na drugim jezicima: hrvatski

Posjeta: 2.453 *