To reduce the ripple of the magnetic flux and torque of motors and the reduce the hysteresis in motor speed control, an improved grey model predictive fuzzy direct torque control (DTC) method based on function transformation is proposed. First, a function transformation is used to transform the sampled sequences to nonnegative values. This overcomes the disadvantages caused by fluctuant and random sampling of the motor torque and stator flux linkage. Second, an equal dimensional new information model is used to keep the dimensions unchanged, which reduces the time to predict the motor parameters through the model. Moreover, the voltage space vector plane is divided into six sectors, which simplifies the fuzzy control system rules. Simulation results show that the proposed fuzzy direct torque control based on the improved grey model method reduces the influence of hysteresis on the control system, decreases the motor flux chain and torque ripple, improves the response speed of the torque and rotational speed, reduces overshoot, achieves good effects in terms of anti-interference capability and dynamic response, and improves the real-time performance and accuracy of the fuzzy control system.

为了减小电动机的磁通量和转矩的波动并减小电动机速度控制中的磁滞，提出了一种基于函数变换的改进的灰色模型预测模糊直接转矩控制方法。首先，使用函数转换将采样序列转换为非负值。这克服了由电动机转矩和定子磁链的波动和随机采样引起的缺点。其次，使用等维新信息模型来保持尺寸不变，这减少了通过模型预测电动机参数的时间。此外，电压空间矢量平面分为六个扇区，从而简化了模糊控制系统规则。