基于神经网络的电动机间接矢量控制系统

Indirect Vector Control System of Induction Motor Drive Based ANN

电动机在一定的负载下以一定的电压、一定的频率时,可以工作在最好的状态。本文提出了用人工智能神经网络预测当负载转矩和速度变化时的工作电压和频率,提高了电动机的效率。实验结果表明,该方法改善了控制系统的鲁棒性,提高了网络学习能力,改善了学习性能,在神经网络控制中有一定推广价值。

Motor works on best performance at certain voltage and frequency for certain loads. In this paper artificial neural network is used to predict the operating voltage and frequency when the load torque and speed going changed so motor efficiency is increased. experimental results are shown to validate the scheme.