Construction of Rotor/AMB dynamic model applied for TMP using self-tuning Kalman Filter

• Fuzzy Logic Adaptive Kalman Filter for system identification is proposed.
• FLAC-EKF has been verified to exhibit fast convergence rate with limited error.
• Intensive experiments have been undertaken to examine the efficacy of FLAC-EKF.

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.