Robust Q-parametrisation control for nonlinear magnetic bearing systems with imbalance based on TSK fuzzy model

M. Fekry, Abdelfatah M. Mohamed, Mohammed Fanni

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)

Abstract

This paper presents a methodology for designing a robust gain scheduled Takagi-Sugeno-Kang (TSK) fuzzy Q-parametrisation controller for nonlinear magnetic bearing systems subjected to imbalance sinusoidal disturbance. First, the mathematical model of nonlinear magnetic bearing is presented. Second, a set of Q-parametrisation observer based stabilising controllers is obtained based on linearisation of the nonlinear system at different operating points. Third, the structure that combines the Q-parametrisation observer based controller (OBC) with TSK fuzzy modelling to overcome the model nonlinearity and expand the operating envelopes is explained. Fourth, the proposed controller is applied to a nonlinear magnetic bearing system. Finally, the simulation results are presented. The results clearly show that the proposed controller is able to merge the intelligence of fuzzy systems with robustness of Q-parametrisation control to extend operating range up to more than 80% of gap length and reject imbalance sinusoidal disturbances at different operating speeds.

Original languageEnglish
Pages (from-to)195-208
Number of pages14
JournalInternational Journal of Modelling, Identification and Control
Volume29
Issue number3
DOIs
Publication statusPublished - 2018
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Modelling and Simulation
  • Computer Science Applications
  • Applied Mathematics

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