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Research on PMSM Sensorless Control Based on Improved RBF Neural Network Algorithm

机译:基于改进RBF神经网络算法的PMSM无传感器控制研究

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In this paper, a method of realizing PMSM sensorless control based on the improved radial basis function (RBF) neural network and high-frequency injection method is studied. The scheme uses the high-frequency injection method to realize the sensorless detection of the rotor position and speed, and adjusts the PI controller parameters online through the improved RBF neural network. The high-frequency injection method can realize the rotor position detection including zero speed. The improved RBF neural network can adjust the changes of hidden nodes online to obtain the best network structure, and can optimize the learning rate in real time to adjust the PI controller parameters. Finally, the experimental simulation is carried out. The results show that the scheme proposed in this paper can detect the position and speed of the PMSM rotor accurately, with fast response speed and good dynamic and static performance.
机译:本文研究了一种基于改进的径向基函数神经网络和高频注入法的永磁同步电机无传感器控制的实现方法。该方案采用高频注入法实现转子位置和速度的无传感器检测,并通过改进的RBF神经网络在线调整PI控制器参数。高频注入法能够实现零速的转子位置检测。改进的RBF神经网络可以在线调整隐藏节点的变化以获得最佳的网络结构,并可以实时优化学习率以调整PI控制器参数。最后,进行了实验仿真。结果表明,本文提出的方案可以准确地检测出永磁同步电动机转子的位置和速度,响应速度快,动静性能好。

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