| MRAS感应电机定子电阻的在线辨识 |
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| 引用本文： | 李健,程小华.MRAS感应电机定子电阻的在线辨识[J].电机与控制学报,2007,11(6):620-624. |
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| 作者姓名： | 李健 程小华 |
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| 作者单位： | 华南理工大学,电力学院,广东,广州,510640 |
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| 摘 要： | 针对感应电机定子电阻值受外界因素干扰而影响其矢量控制系统稳定性和控制精确度问题,提出了基于人工神经网络的定子电阻在线辨识方法.为了辨识定子电阻,将人工神经网络模型的定子电流估算值与实际测量电流值的误差反馈以调整神经网络的权值.借助MATLAB/SIMULINK搭建仿真系统,验证了定子电阻在线辨识的必要性.结果表明,该方法可以有效地对定子电阻进行在线辨识.
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| 关 键 词： | 人工神经网络 感应电机 定子电阻 在线辨识 无速度传感器 |
| 文章编号： | 1007-449X（2007）06-0620-05 |
| 收稿时间： | 2007-05-28 |
| 修稿时间： | 2007年5月28日 |
Online identification based on model reference adaptive system for stator resistance of induction motor |
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| LI Jian,CHENG Xiao-hua.Online identification based on model reference adaptive system for stator resistance of induction motor[J].Electric Machines and Control,2007,11(6):620-624. |
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| Authors: | LI Jian CHENG Xiao-hua |
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| Abstract: | A novel online identification scheme based on artificial neural networks for stator resistance of induction motor is proposed in order to solve the affect on stability and precision by stator resistance variation in induction motor vector control system.For the stator resistance identification,the error between the measured stator current and the estimated stator current based on artificial neural network(ANN) is back propagated to adjust the weights of the neural network.Simulation systems are built with the help of MATLAB/SIMULINK,and the necessity of stator resistance identification are verified.The results show that the stator resistance can be identified online effectively with the proposed scheme. |
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| Keywords: | artificial neural networks induction motor stator resistance online identification speed sensorless |
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