Robust Q-parametrisation control for nonlinear magnetic bearing systems with imbalance based on TSK fuzzy model. (2018)

• Record Type: Journal Article
• Authors: Fekry, M.; Mohamed, Abdelfatah M.; Fanni, Mohammed
• Is Part Of: International journal of modelling, identification and control. Volume 29:Number 3(2018)
• Page Start: 195
• Page End: 208
• Publication Date: 2018
• Subjects: parallel distribution control -- intelligent control -- robust control -- robust stability -- fuzzy supervision -- fuzzy modelling -- Q-parameterisation -- imbalance disturbance rejection -- magnetic bearings modelling -- magnetic bearings control; Engineering -- Methodology -- Periodicals; Science -- Methodology -- Periodicals; 001.42
• Languages: English
• ISSNs: 1746-6172

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.