This study presents design and hardware implementation of cascade neural network (NN)
based flux estimator using field programmable gate array (FPGA) for speed estimation in …

The paper presents the results of our research on the use of artificial neural networks for
sensorless control of induction motor drives. A feedforward artificial neural network with one …

This paper presents a new neural network based model reference adaptive system (MRAS)
to solve low speed problems for estimating rotor resistance in vector control of induction …

In this paper, a new reference model adaptive system based speed estimator is proposed for
multilevel inverter fed sensorless field oriented controlled induction motor drive. The …

The performance of sensor-less direct vector controlled IM drives to a large extent depends
on the accuracy of field angle and resultant flux estimation. This in turn depends on the …

The accurate estimation of magnitude and angle of flux is vital for good performance of
Direct Flux/Field Oriented Control (DFOC) of Asynchronous Motor (AM)/Induction Motor (IM) …

The major advantages of sensorless induction motor drives are reliability and low cost due
to exclusion of sensors. The sensorless schemes proceed with the speed estimate and other …

This paper proposes a Model Reference Adaptive Control (MRAC) which makes use of both
back EMF and Reactive Power methods for sensorless rotor speed measurement against …