BSRM rotor unbalance vibration compensation control method based on EKF

Abstract

The invention discloses a BSRM rotor unbalance vibration compensation control method based on EKF. The method comprises steps that a BSRM state space model is established, and linearization and discretization are carried out; a discrete linear state space equation is substituted into the EKF for recursive calculation, a covariance matrix P and a Kalman gain matrix K in the EKF in real time are updated, and a state variable is further updated; the EKF estimates a rotor actual displacement signal and an unbalanced vibration displacement signal in real time while weakening random interference andmeasurement noise in a BSRM rotor stability control process; the unbalanced vibration displacement signal obtained through EKF estimation is compensated to the displacement signal obtained through EKF estimation in real time, so the unbalanced vibration quantity in the displacement feedback signal is eliminated, a control system does not generate corresponding unbalanced control force, and a purpose of reducing stator vibration is achieved. The method is advantaged in that not only can BSRM displacement measurement noise and random interference be effectively filtered, but further the unbalanced control force of the BSRM can be effectively reduced.

Description

technical field [0001] The invention belongs to the technical field of active balance control of rotating equipment, and in particular relates to an extended Kalman filter (EKF)-based rotor unbalance vibration compensation control method for a bearingless switched reluctance motor (BSRM). Background technique [0002] In rotating machinery, especially in high-speed bearingless switched reluctance motors (BSRM), the unbalanced mass of the rotor will cause centrifugal force with the same frequency as the rotational speed, resulting in unbalanced vibration; at the same time, the magnetic pull that reacts on the stator will also increase, thereby causing vibration and noise of the BSRM stator casing. In addition, in the BSRM system, due to the existence of hardware noise such as sensor noise, the actual measured rotor displacement signal will contain a large amount of high-frequency random noise, which will affect the control accuracy and further reduce the operating performance...

AI Technical Summary

Problems solved by technology

Although the notch filter based on the LMS algorithm has a strong ability to suppress unbalanced vibration, the algorithm can only filter out fixed frequency signals, and the existence of random interference and measurement noise will affect the filtering effect. In the presence of noise and noise, the algorithm is difficult to effectively compensate for the unbalanced vibration of the BSRM rotor

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