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针对运用传统模型的灰色预测模糊直接转矩控制系统中电机转矩和定子磁链采样值时间序列非单调、波动性强和随机性强等缺点,提出采用一种基于新陈代谢思想的灰色Verhulst模型用以实现电机参数预测.通过对采样值序列进行区间比例变换完成序列非负化;运用等维新息模型保证建模序列的维数不变,并经灰色Verhulst模型预测得出下一状态电机定子磁链、转矩和磁链位置角;将磁链位置角作为模糊输入变量,采取分扇区处理方式减少模糊控制器的模糊规则数量.仿真结果表明,采用基于改进的灰色Verhulst模型的预测模糊直接转矩控制系统可以进一步提高模型的预测精度,降低电机的磁链与转矩的脉动,提高转矩与转速的响应速度,降低了超调量.
Aimed at the shortcomings of gray prediction fuzzy direct torque control system using traditional model, the time series of motor torque and stator flux sampling are non-monotonous, strong volatility and strong randomness, a gray Verhulst model based on metabolic theory is proposed In order to realize the prediction of the motor parameters, the sequence non-negative sequence is obtained by interval-proportional transformation of the sample sequence, the dimension of the modeling sequence is guaranteed by using the equal-dimensional information model, and the next state motor stator magnet is predicted by the gray Verhulst model The position of chain flux, the flux and the position of flux linkage are taken as the fuzzy input variables, and the sector-based processing is adopted to reduce the number of fuzzy rules of the fuzzy controller.The simulation results show that the fuzzy prediction based on the improved gray Verhulst model Torque control system can further improve the prediction accuracy of the model, reduce motor flux and torque ripple, improve the response speed of torque and speed, reduce overshoot.