An intelligent Q-parameterization control design that captures non-linearity and fuzziness of uncertain magnetic bearing system

M. Fekry, Abdelfatah M. Mohamed, M. Fanni

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

3 Citations (Scopus)

Abstract

This paper presents a systematic procedure to design a robust gain scheduled Q-parametrization Takagi-Sugeno (TS) fuzzy controller for non-linear magnetic bearing system with imbalance. First, a mathematical model of non-linear magnetic bearing model is presented. Second, the system is linearized around various operating points to overcome the model non-linearity by increasing the operating envelop. Third, the Q-parametrization observer based stabilizing controller with TS fuzzy systems is explained which combines both the intelligence of fuzzy systems and robustness of Q-parametrization. Forth, the proposed controller is applied to a non-linear magnetic bearing system. Finally, the simulation results are presented. The results manifest the ability of proposed controller to overcome the model non-linearity by increasing the dynamic operating range up-to more than 80% of gap length and reject imbalance disturbances under different speeds.

Original languageEnglish
Title of host publication2015 IEEE Conference on Control and Applications, CCA 2015 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1078-1083
Number of pages6
ISBN (Electronic)9781479977871
DOIs
Publication statusPublished - Nov 4 2015
Externally publishedYes
EventIEEE Conference on Control and Applications, CCA 2015 - Sydney, Australia
Duration: Sep 21 2015Sep 23 2015

Publication series

Name2015 IEEE Conference on Control and Applications, CCA 2015 - Proceedings

Other

OtherIEEE Conference on Control and Applications, CCA 2015
CountryAustralia
CitySydney
Period9/21/159/23/15

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering

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