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

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

doi:10.1109/ISIC.1994.367837

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

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

School of Engineering & Physical Sciences

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Citation (Scopus)

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 language	English
Title of host publication	Proceedings of the 1994 IEEE International Symposium on Intelligent Control
Pages	81-86
Number of pages	6
DOIs	https://doi.org/10.1109/ISIC.1994.367837
Publication status	Published - 1994
Event	1994 IEEE International Symposium on Intelligent Control - Columbus, OH, USA Duration: 16 Aug 1994 → 18 Aug 1994

Conference

Conference	1994 IEEE International Symposium on Intelligent Control
City	Columbus, OH, USA
Period	16/08/94 → 18/08/94

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10.1109/ISIC.1994.367837

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title = "Fuzzy adaptive systems applied to the control of a switched reluctance motor",

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.",

author = "Reay, {D. S.} and M. Mirkazemi-Moud and Green, {T. C.} and Williams, {B. W.}",

note = "INSPEC Accession Number: 4851284; 1994 IEEE International Symposium on Intelligent Control ; Conference date: 16-08-1994 Through 18-08-1994",

year = "1994",

doi = "10.1109/ISIC.1994.367837",

language = "English",

isbn = "0-7803-1990-7",

pages = "81--86",

booktitle = "Proceedings of the 1994 IEEE International Symposium on Intelligent Control",

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T1 - Fuzzy adaptive systems applied to the control of a switched reluctance motor

AU - Reay, D. S.

AU - Mirkazemi-Moud, M.

AU - Green, T. C.

AU - Williams, B. W.

N1 - INSPEC Accession Number: 4851284

PY - 1994

Y1 - 1994

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=0028727267&partnerID=8YFLogxK

U2 - 10.1109/ISIC.1994.367837

DO - 10.1109/ISIC.1994.367837

M3 - Conference contribution

SN - 0-7803-1990-7

SP - 81

EP - 86

BT - Proceedings of the 1994 IEEE International Symposium on Intelligent Control

T2 - 1994 IEEE International Symposium on Intelligent Control

Y2 - 16 August 1994 through 18 August 1994

ER -

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

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