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.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: International Journal of Modelling, Identification and Control
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
