ANN based sensorless vector controlled induction motor drive suitable for four quadrant operation

R. Verma, Vimlesh Verma, C. Chakraborty
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引用次数: 8

Abstract

In this paper an artificial neural network (ANN) based speed estimator is presented for vector-controlled squirrel cage induction motor (IM) drive. The drive is stable in all operating region and is independent of stator resistance variation. Stator currents, modified stator voltages (Reference values) with stator resistance adaption are used as input to the ANN and rotor speed is treated as the output. For ANN training, Levenberg-Marquardt algorithm is used. Network is first trained for different test data. Finally the algorithm is tested for motoring and regenerating mode considering various loads, speed levels including effect of stator resistance variation. The proposed method is validated through computer simulation using MATLAB/SIMULINK environment.
基于人工神经网络的四象限无传感器矢量控制感应电机驱动
提出了一种基于人工神经网络的矢量控制鼠笼式异步电动机转速估计方法。该驱动器在所有工作区域稳定,不受定子电阻变化的影响。定子电流、经定子电阻自适应的修正定子电压(参考值)作为人工神经网络的输入,转子转速作为输出。对于人工神经网络的训练,使用Levenberg-Marquardt算法。首先针对不同的测试数据对网络进行训练。最后对该算法进行了考虑各种负载、转速水平及定子电阻变化影响的电机和再生模式的测试。通过MATLAB/SIMULINK环境下的计算机仿真验证了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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