Identification of Rotor System Parameters of Maglev Motor Based on Gaussian Modulation Function

A stiffness parameter identification method based on Gaussian modulation function is proposed to solve the problem that the stiffness parameter of the rotor system of maglev motor is not accurate in the process of suspension control, which affects the improvement and optimization of the controller and even causes the instability of the system. Firstly, the rotor system of maglev motor is stabilized in a closed loop under PID control, and then the continuous dynamic model of maglev motor rotor system is digitally modulated and integrated by using Gaussian function as modulation function, so as to establish a discrete equivalent parameter identification model. Then, the scale parameters matching the frequency band coverage of the magnetic levitation motor rotor system are selected to construct the Gaussian modulation function, and the stiffness parameters of the maglev motor rotor system are identified. The simulation and experimental results show that the proposed method avoids the direct processing of differential signal and the problem of initial integral value, and can easily and effectively identify the stiffness parameters of the rotor system of the maglev motor.