基于模糊神经网络的永磁同步电动机矢量控制系统

该文提供了一种基于自适应模糊神经网络的永磁同步电动机（PMSM）矢量控制系统速度控制器的实施方案。模糊神经网络控制器（FNNC）包括神经网络控制器（NC）和模糊逻辑控制器（FC）两部分，它同时具有神经网络自学习能力和模糊逻辑在处理不确定信息方面的能力。人工神经网络（ANN）的初始权值和阈值通过离线训练的方式获得。在实际的运行过程中，利用模糊控制器的输出对神经网络的权值和阈值进行实时调整。仿真结果表明利用所提出的模糊神经网络来建立永磁同步电动机矢量控制系统的速度控制器，当电机参数改变或者受到外部扰动时，系统具有良好的动态特性。

Vector Controlled Permanent Magnet Synchronous Motor Drive with Adaptive Fuzzy Neural Network Controller

This paper presents the implementation of adaptive fuzzy neural network controller(FNNC)for accurate speed control of a permanent magnet synchronous motor(PMSM).FNNC includes neural network controller(NC)and fuzzy logic controller(FC).It combines the capability of fuzzy reasoning in handling uncertain information and the capability of neural network in learning from processes.The initial weights and biases of the artificial neural network(ANN)are obtained by offline training method.Using the output of the fuzzy controller,online training is carried out to update the weights and biases of the ANN.The results of simulation and experiment are provided to demonstrate the effectiveness of the proposed FNNC under the occurrence of parameter variations and external disturbance.