Linear Induction Motor Drives Based on Linear
Neural Networks
IEEE TRANSACTIONS ON POWER ELECTRONICS, VOL. 28, NO. 1, JANUARY 2013
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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-mode MRAS speed observers
developed for the rotating machines.
Index Terms—Field-oriented control (FOC), linear induction
motor (LIM), model reference adaptive systems (MRASs), neural
networks (NNs), sensorless control.
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