Switched reluctance motor control with artificial neural networks

Abstract

This paper presents a new control scheme for switched reluctance motor drives based on artificial neural networks (ANN). The ANNs are trained to generate drive circuitry phase current references for velocity reference tracking. A new, application specific ANN architecture is used to improve modeling accuracy. The control ANNs are trained using data from a state space model. The control scheme characteristics are then presented via two case studies. Firstly, a constant velocity control is simulated and a comparison with previously measured results is presented. A velocity reference tracking case study is then presented.