DIRECT TORQUE CONTROL OF THE GENETIC NEURAL NETWORK UNDER THE LOW-SPEED

摘要

For the direct torque control of asynchronous motor rapid response and speed ripple, this article proposes the genetic neural network algorithm based on the model of stator flux, to achieve the selecting of switch state under the low-speed. Using the global optimization and search method of genetic algorithm obtains global optimal solution, while the connection weights and network structure learning improve the training effectiveness of neural network, so that the BP network has better adaptive characteristic. The effectiveness of the design is verified by the simulation, and it shows that the speed control system has good dynamic performance and steady state performance under the low-speed.