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Induction Motor Identification Using Elman Neural Network

机译:基于Elman神经网络的感应电动机识别

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In this paper, we study an induction motor identification in all states and conditions whether transient or steady using Elman neural network. Induction motors have highly nonlinear dynamic behaviours where the parameters vary with time and operating conditions. These nonlinear dynamic behaviours make difficult the identification of induction motor. While many applications such as control [1] need an accurate identification of induction motor, therefore having an appropriate identification seems to be necessary. Here a recurrent neural network introduced by Elman [2] which has the ability of learning temporal patterns as well as spatial ones is employed for induction motor identification. Our experiments show that using Elman recurrent neural network for identification could achieve high degree of accuracy in all states and conditions.
机译:在本文中,我们研究了使用Elman神经网络在所有状态和条件下,无论是瞬态还是稳态的感应电动机识别。感应电动机具有高度非线性的动态行为,其中参数随时间和工作条件而变化。这些非线性动力学行为使得感应电动机的识别变得困难。尽管许多应用程序,例如控制[1],都需要准确识别感应电动机,但是似乎有必要进行适当的识别。这里,由Elman [2]引入的具有学习时间模式和空间模式能力的递归神经网络被用于感应电机识别。我们的实验表明,使用Elman递归神经网络进行识别可以在所有状态和条件下实现较高的准确性。

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