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Simulation Model of Magnetic Levitation Based on NARX Neural Networks

机译:基于NARX神经网络的磁悬浮仿真模型

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In this paper, we present analysis of different training types for nonlinear autoregressive neural network, used for simulation of magnetic levitation system. First, the model of this highly nonlinear system is described and after that the Nonlinear Auto Regressive eXogenous (NARX) of neural network model is given. Also, numerical optimization techniques for improved network training are described. It is verified that NARX neural network can be successfully used to simulate real magnetic levitation system if suitable training procedure is chosen, and the best two training types, obtained from experimental results, are described in details.
机译:在本文中,我们介绍了非线性自回归神经网络的不同训练类型的分析,用于磁悬浮系统的仿真。首先,描述了该高度非线性系统的模型,然后给出了神经网络模型的非线性自回归异质(NARX)。另外,描述了用于改进网络训练的数值优化技术。验证了如果选择合适的训练程序,NARX神经网络可以成功地用于模拟真实的磁悬浮系统,并详细描述了从实验结果中获得的最佳两种训练类型。

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