Novel fuzzy direct torque control based on constructed functional transformed grey model

Abstract

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.