Original scientific paper
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
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 + 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.
Keywords
induction motor drives; sensorless control; model reference adaptive systems; neural networks
Hrčak ID:
6842
URI
Publication date:
21.12.2005.
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