BP神经网络辩识感应电机转子磁链和转速

根据感应电机数字模型，提出了仅基于定子电流的人工神经网络转子磁链与速度的辩识方法，实现无速度传感器的交流调速系统的转子磁链和转速闭环控制。用BP算法对神经网络进行学习和训练，构建相应的多层前馈神经网络（MFNN）。仿真和实验结果表明，这种转子磁链与速度的辩识模型具有良好的性能。

Rotor Flux and Speed Estimation of Induction Motor Using BP Neural Network

Sensorless vector control of the induction motor with closed loop of rotor flux and speed requires the know ledge of instantaneous magnitude and position of the rotor flux as well as rotor speed. This paper deals with the identification of the rotor flux and speed on the base of stator phase current and the delayed one. According to the fundamental equations of induction motor for vector control, the novel identification method of rotor flux and speed using neural network is presented. The structure of multi layer feed forward neural networks is trained with Back Propagation Levenberger Marquardt's method. The simulation and experiment results show the system with neural network identification model has better Performance.