Adaptive Fuzzy Kalman Filter Applied for Identification of Rotor/Active Magnetic Bearing Dynamics

Yu-Hsun Liu, Nan-Chyuan Tsai, and Hsin-Lin Chiu

Keywords

Active Magnetic Bearing, System Identification, Kalman Filter, Fuzzy Logic Algorithm

Abstract

The main goal of this research is to identify the system parameters of the dynamics of Rotor/Active Magnetic Bearing (Rotor/AMB) system employed in turbo molecular pumps (TMPs). The identification approach adopted in this work is based on experimental analysis and the application of Fuzzy Logic Adaptive Control-Extended Kalman Filter (FLAC-EKF). The estimation error for either system state or system parameters can be gradually converged to zero via self-tuning of the design parameters of FLAC-EKF. The proposed algorithm has been verified by numerical simulations and intensive experiments. It is concluded that the FLAC-EKF can exhibit satisfactory performance in terms of estimation accuracy on the system parameters even under contamination of a certain degree of process disturbance and sensor noise.

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