基于FPGA的无刷直流电机控制系统探讨

Discussion on Control System of Brushless DC Motor Based on FPGA

无刷直流电机由于具有起动和调速性好,控制简单和堵转转矩大等特点,在驱动和伺服系统中广泛应用。但使用位置传感器检测转子的位置信息存在增加成本和电机难以在高低温环境下工作等问题。因此探讨了以卷积神经网络作为基础模型,并使用FPGA加速器的无刷直流电机控制系统的设计思路以及优化策略,以实现无刷直流电机的自适应控制。

Brushless DC motor(BLDCM)is widely used in drive and servo system because of its good starting and speed regulation,simple control and large torque blocking.However,the use of position sensor to detect rotor position information makes the motor volume increase,the connection increase introduces interference,and it is difficult to work in high and low temperature environment.Based on the Convolutional Neural Network(CCN)model,this paper discusses the design idea and optimization strategy of BLDCM control system using Field-programmable Gate Array(FPGA)accelerator to realize adaptive control of BLDCM.