Efficiency improvements in switched reluctance motor position and torque control using adaptive fuzzy systems

D. S. Reay, C. Shang, B. W. Williams

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

4 Citations (Scopus)

Abstract

Switched and variable reluctance motors are well suited to use in direct-drive torque and position control of robotic actuators but suffer from nonlinear torque production characteristics. It has been demonstrated that adaptive fuzzy systems are capable of learning nonlinear current waveforms suitable for linearisation of the torque production characteristics in switched reluctance motors. This paper reports an investigation into the use of an extended heuristic method in order to produce solutions to the torque ripple minimisation problem that are particularly efficient with respect to copper losses. Simulation results based on experimentally measured data are presented demonstrating the influence of modified learning rate functions on the solutions learned by an adaptive fuzzy system and that these compare favourably with optimal solutions.

Original languageEnglish
Title of host publicationIEEE International Conference on Fuzzy Systems
Subtitle of host publicationProceedings of the 1996 5th IEEE International Conference on Fuzzy Systems. Part 3 (of 3); New Orleans, LA, USA; ; 8 September 1996 through 11 September 1996
Pages800-805
Number of pages6
Volume2
Publication statusPublished - 1996
EventProceedings of the 1996 5th IEEE International Conference on Fuzzy Systems. Part 3 (of 3) - New Orleans, LA, USA
Duration: 8 Sep 199611 Sep 1996

Conference

ConferenceProceedings of the 1996 5th IEEE International Conference on Fuzzy Systems. Part 3 (of 3)
CityNew Orleans, LA, USA
Period8/09/9611/09/96

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  • Cite this

    Reay, D. S., Shang, C., & Williams, B. W. (1996). Efficiency improvements in switched reluctance motor position and torque control using adaptive fuzzy systems. In IEEE International Conference on Fuzzy Systems: Proceedings of the 1996 5th IEEE International Conference on Fuzzy Systems. Part 3 (of 3); New Orleans, LA, USA; ; 8 September 1996 through 11 September 1996 (Vol. 2, pp. 800-805)