Control of dual acting magnetic bearing actuator system using fuzzy logic

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15 Citations (Scopus)

Abstract

In this paper, a fuzzy logic scheme is developed to improve the performance of a magnetic bearing control system. The developed fuzzy logic strategy is utilized in the non-linear control of a dual-acting magnetic bearing actuator system. The mathematical model of a dual acting magnetic bearing axis has been developed. The non-linearity in this system is due to the relationship between the forces generated in the electromagnetic actuator and the coil current and the air gap between the rotor and the stator. Non-linearities in magnetic bearing systems limit the control effectiveness and the region of stable performance. The model is used for dynamic simulation purposes and it is not directly used in the fuzzy controller design. Active magnetic bearing with adaptive fuzzy control showed a good improvement in step response compared to a linear PID or a steady state controller. With the presented fuzzy logic based strategy, nonlinear controllers for nonlinear applications can be designed with little effort.

Original languageEnglish
Title of host publicationProceedings - 2003 IEEE International Symposium on Computational Intelligence in Robotics and Automation
Subtitle of host publicationComputational Intelligence in Robotics and Automation for the New Millennium
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages97-101
Number of pages5
Volume1
ISBN (Electronic)0780378660
DOIs
Publication statusPublished - 2003
Event2003 IEEE International Symposium on Computational Intelligence in Robotics and Automation, CIRA 2003 - Kobe, Japan
Duration: 16 Jul 200320 Jul 2003

Other

Other2003 IEEE International Symposium on Computational Intelligence in Robotics and Automation, CIRA 2003
CountryJapan
CityKobe
Period16/07/0320/07/03

All Science Journal Classification (ASJC) codes

  • Computational Mathematics

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    Habib, M. K., & Inayat Hussain, J. I. (2003). Control of dual acting magnetic bearing actuator system using fuzzy logic. In Proceedings - 2003 IEEE International Symposium on Computational Intelligence in Robotics and Automation: Computational Intelligence in Robotics and Automation for the New Millennium (Vol. 1, pp. 97-101). [1222070] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CIRA.2003.1222070