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

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.