Direct Torque Control System Based on Neural Network Restructuring Model

The direct torque control is a novel high-powered AC frequency control techniques after the converter technique based on the vector control.Aiming at the problems of great current and torque ripple of the asynchronous motor based on direct torque control when it is running at low-speed.This paper uses neural-network to restructuring stator flux observer and status selector model in direct torque control system.And uses the individual training neural-network to cope with the complex calculations.The simulating result shows that the system using the neural-network have good dynamic performance and efficiently improve the low-speed performance of direct torque control system.