Investigation on advanced control of a linear switched reluctance motor

Y. Zou, K. W.E. Cheng, N. C. Cheung

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

Abstract

Advanced control systems are increasingly employed for intelligent factories. Fuzzy logic control (FLC) and backward propagation neural network (BPNN) control are investigated in this paper to realize position control for a linear switched reluctance motor (LSRM) against its nonlinear characteristics. Principles for FLC and BPNN control are introduced elaborately. Simulation results via BPNN show that dynamic position errors for the LSRM can be limited to 0.1 mm. Experimental results on FLC suggest that point-to-point position tracking for the motor can achieve 0.01 mm, constraining dynamic position error in 0.1 mm. By experiments, FLC for the LSRM performs better than traditional proportional-integral-derivative (PID) control, proving the effectiveness of the alleviation of the nonlinearity for the LSRM.

Original languageEnglish
Title of host publication2017 7th International Conference on Power Electronics Systems and Applications - Smart Mobility, Power Transfer and Security, PESA 2017
EditorsK.W. Eric Cheng
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-6
Number of pages6
ISBN (Electronic)9781538613863
DOIs
Publication statusPublished - 31 Jan 2018
Event7th International Conference on Power Electronics Systems and Applications - Smart Mobility, Power Transfer and Security, PESA 2017 - Hong Kong, Hong Kong
Duration: 12 Dec 201714 Dec 2017

Publication series

Name2017 7th International Conference on Power Electronics Systems and Applications - Smart Mobility, Power Transfer and Security, PESA 2017
Volume2018-January

Conference

Conference7th International Conference on Power Electronics Systems and Applications - Smart Mobility, Power Transfer and Security, PESA 2017
CountryHong Kong
CityHong Kong
Period12/12/1714/12/17

Keywords

  • backward propagation neural network
  • Fuzzy logic control
  • LSRM
  • position tracking

ASJC Scopus subject areas

  • Artificial Intelligence
  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering
  • Safety, Risk, Reliability and Quality

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