Data Driven Motor Control Based on Auto Associative Kernel Regression Algorithm
In the field of motor control,the model-driven control method has been widely studied.With the improvement of computer computing power,it brings the possibility to calculate a large number of data.In order to further improve the motor control performance,a control compensation strategy based on Auto Asso-ciative Kernel Regression(AAKR)algorithm was studied to correct and compensate the motor control process based on a large number of data during operation,so as to improve the motor control performance,smooth out fluctuations during operation.Through theoretical and simulation analysis,the method can com-plete the motor operation control well,and the compensated control strategy can reduce the current fluctua-tion and torque ripple,and has a certain control compensation effect.This control algorithm is also applica-ble to the optimization process of other motor control strategies,and has a certain reference value.
auto associative kernel regressionmotor controlcompensation correctiondata driven
万方数据
维普
