6533b857fe1ef96bd12b4cbd

RESEARCH PRODUCT

MRAS speed observer for high performance linear induction motor drives based on linear neural networks

Angelo AccettaGianpaolo VitaleMarcello PucciMaurizio Cirrincione

subject

EngineeringObserver (quantum physics)Artificial neural networkDiscretizationControl theorybusiness.industryAdaptive systemLinear induction motorbusinessMRASStationary Reference FrameMachine control

description

This paper proposes a Neural Network (NN) MRAS (Model Reference Adaptive System) speed observer suited for linear induction motor (LIM) drives. The voltage and current models of the LIM in the stationary reference frame, taking into consideration the end effects, have been obtained. Then, equations of the induced part have been discretized and rearranged so as to be represented by a linear neural network the TLS EXIN neuron, which has been used to compute the machine linear speed on-line and in recursive form. The proposed NN MRAS observer has been tested experimentally on a suitably developed test setup. Its performance has been also compared to the classic MRAS speed observer.

yearjournalcountryeditionlanguage
2011-09-012011 IEEE Energy Conversion Congress and Exposition
https://doi.org/10.1109/ecce.2011.6063997