Torque ripple reduction in switched reluctance motor drives using B-spline neural networks

Zhengyu Lin, Donald S. Reay, Barry W. Williams, Xiangning He

Research output: Contribution to journalArticle

46 Citations (Scopus)

Abstract

A switched reluctance motor torque ripple reduction scheme using a B-spline neural network (BSNN) is presented. Closed-loop torque control can be implemented using an on-line torque estimator. Due to the local weight updating algorithm used for the BSNN, an appropriate phase current profile for torque ripple reduction can be obtained on-line in real time. It has good dynamic performance with respect to changes in torque demand. The scheme does not require high-bandwidth current controllers. Simulation and experimental results demonstrate the validity of the scheme. © 2006 IEEE.

Original languageEnglish
Pages (from-to)1445-1453
Number of pages9
JournalIEEE Transactions on Industry Applications
Volume42
Issue number6
DOIs
Publication statusPublished - Nov 2006

Keywords

  • Neural networks
  • Reluctance motors
  • Torque control

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