Simulation Model of Magnetic Levitation Based on NARX Neural Networks
Автор: Dragan Antić, Miroslav Milovanović, Saša Nikolić, Marko Milojković, Staniša Perić
Журнал: International Journal of Intelligent Systems and Applications(IJISA) @ijisa
Статья в выпуске: 5 vol.5, 2013 года.
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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.
Neural Network, Magnetic Levitation System, Nonlinear Model, Neural Network Training
Короткий адрес: https://sciup.org/15010418
IDR: 15010418
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