Permanent magnet synchronous motor rotating speed control method based on optimized grey prediction compensation

Abstract

The invention relates to a permanent magnet synchronous motor rotating speed control method based on optimized grey prediction compensation. As for the influences brought by uncertain factors such as noise and microvariations on permanent magnet synchronous motor rotating speed control precision, a grey system theory is adopted to build a grey prediction model to carry out advanced prediction on rotating speed deviation produced by disturbance terms, then real-time compensation is carried out on an actual control process, and rotating speed tracking performance and robustness of a permanent magnet synchronous motor are improved. Due to the fact that a traditional grey method has inherent defects in the initial value selecting aspect, the optimized grey prediction model is provided at first and then is applied into motor rotating speed control. The optimized grey prediction model is obtained through grey model derivation, the grey model is used for predicting the future rotating speed deviation of the permanent magnet synchronous motor on the basis of vector control, advanced prediction compensation is carried out, and the motor rotating speed control precision and robustness are improved.

Description

technical field [0001] The invention belongs to a speed control method of a permanent magnet synchronous motor, in particular to a speed control method of a permanent magnet synchronous motor based on optimized gray prediction compensation. Background technique [0002] At present, the electric drive systems of new aerospace vehicles such as solar unmanned aerial vehicles and multi-electric aircraft have high requirements on control performance, and permanent magnet synchronous motors as a drive device have high power density, small size, reliable operation, and convenient maintenance. characteristics have received widespread attention. However, when controlling the speed of permanent magnet synchronous motors, it is often affected by uncertain factors such as noise, operating environment, temperature, parameter changes, and load disturbances, so it is difficult to establish a definite permanent magnet synchronous motor speed control model. [0003] Uncertain disturbance it...

AI Technical Summary

Problems solved by technology

However, the gray forecasting method is sensitive to the selection of the initial value. The traditional method takes the initial value as the first value of the original sequence, but with the real-time update of the forecast value, such an initial value cannot reflect the actual forecast situation, and the As the prediction length increases, the distance from the initial value is getting farther and farther, and the regularity is weakened

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