Title: Neural fuzzy control to minimise torque ripple of SRM

Authors: Jian Liu, Feng Qiao, Meiju Liu, Chengdong Wu

Addresses: Faculty of Information and Control Engineering, Shenyang Jianzhu University, 9 Hunnan East Road, Hunnan New District, Shenyang, Liaoning, 110168, China; Faculty of Information Science and Engineering, Northeastern University, 3 Wenhua Road, Heping District, Shenyang, Liaoning, 110004, China. ' Faculty of Information and Control Engineering, Shenyang Jianzhu University, 9 Hunnan East Road, Hunnan New District, Shenyang, Liaoning, 110168, China. ' Faculty of Information and Control Engineering, Shenyang Jianzhu University, 9 Hunnan East Road, Hunnan New District, Shenyang, Liaoning, 110168, China. ' Faculty of Information Science and Engineering, Northeastern University, 3 Wenhua Road, Heping District, Shenyang, Liaoning, 110004, China

Abstract: The switched reluctance motor (SRM) exhibits high non-linear characteristics, so it is difficult to employ conventional control algorithms to achieve the desired dynamic performances for non-linear SRMs. It is proposed, in this paper, a new kind of neural fuzzy controller to tackle the problem of torque ripple reduction in switched reluctance motor drive, which does not require the precise mathematical model of the system and offers an obvious advantage over traditional PID control system. The simulation results show that the neural fuzzy control strategy possesses superior performance in reducing low frequency torque ripple and torque dip, and demonstrate the effectiveness and feasibility of the proposed scheme.

Keywords: neural networks; fuzzy control; switched reluctant motors; SRM; torque ripple reduction; simulation.

DOI: 10.1504/IJMIC.2010.033856

International Journal of Modelling, Identification and Control, 2010 Vol.10 No.1/2, pp.132 - 137

Published online: 02 Jul 2010 *

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