Fuzzy adaptive systems applied to the control of a switched reluctance motor

D. S. Reay, M. Mirkazemi-Moud, T. C. Green, B. W. Williams

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper presents the application of fuzzy adaptive systems to the problem of torque ripple reduction in a switched reluctance motor. Conventional methods for torque linearisation and decoupling are reviewed briefly, as is the previous application, by the authors, of neural network based techniques. A solution based on the use of fuzzy adaptive systems is then described. Experimental measurements of the static torque production characteristics of a 4kW, four-phase switched reluctance motor form the basis of simulation studies of this novel approach. The simulation results demonstrate the capability of fuzzy adaptive systems to learn non-linear current profiles that minimise torque ripple. The use of fuzzy systems in this application has potential advantages where the incorporation of a priori information, expressed linguistically, is concerned. Experimental results illustrate the effectiveness of the approach.

Original languageEnglish
Title of host publicationProceedings of the 1994 IEEE International Symposium on Intelligent Control
Pages81-86
Number of pages6
DOIs
Publication statusPublished - 1994
Event1994 IEEE International Symposium on Intelligent Control - Columbus, OH, USA
Duration: 16 Aug 199418 Aug 1994

Conference

Conference1994 IEEE International Symposium on Intelligent Control
CityColumbus, OH, USA
Period16/08/9418/08/94

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  • Cite this

    Reay, D. S., Mirkazemi-Moud, M., Green, T. C., & Williams, B. W. (1994). Fuzzy adaptive systems applied to the control of a switched reluctance motor. In Proceedings of the 1994 IEEE International Symposium on Intelligent Control (pp. 81-86) https://doi.org/10.1109/ISIC.1994.367837