The switched reluctance machine (SRM) is the least expensive electrical machine to
produce, yet one of the most reliable. As such, research has blossomed during the last …

This paper presents a new approach to the sensorless control of the switched-reluctance
motor (SRM). The basic premise of the method is that an artificial neural network (ANN) …

The most advanced vacuum cleaners are now using brushless drives, with operating
speeds in excess of 100 000 r/min. The drives are very sophisticated, but must also be low in …

This paper presents real-time verification of an artificial neural network (ANN) and adaptive
neuro-fuzzy inference system (ANFIS) based rotor position estimation techniques for a 6/4 …

Sensorless position sensing of switched reluctance motor (SRM) has been of great interests
to researchers for reducing costs and increasing reliability of the system. The startup position …

Switched reluctance motors (SRMs) require sensitive rotor information in order to work
sensitively and properly and especially for the commutation of phase currents. Position …

This paper presents an approach to rotor position estimation in switched reluctance motors
(SRMs) by using a cerebellum model articulation controller (CMAC). Previous research has …

Sensorless operation is very crucial to the successful commercial entrance of a majority of
SRM drives. A large number of sensorless (both current and rotor position) control schemes …

In this paper, unipolar excitation-based speed sensorless vector-controlled switched
reluctance motor (SRM) drive is addressed. The use of position/speed sensors has few …

This paper presents a novel approach of single neuron PID control for position sensorless
switched reluctance motors (SRM) based on radial basis function (RBF) neural network. In …