Position sensorless control system of SRM using neural network

This paper presents a position sensorless control system of Switched Reluctance Motor (SRM) using Neural Network. The control of an SRM depends on the commutation of the stator phases in synchronism with the rotor position. The position sensing requirement increases the overall cost and complexity. In this paper, the current-flux-rotor position lookup table based position sensorless operation of a SRM is presented. Neural Network is used to construct the current-flux-rotor position lookup table, and is trained by sufficient experimental data. Experimental results for a 1-hp SRM is presented for the verification of the proposed sensorless algorithm.