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- W2895839163 abstract "Aiming at complex train operation environment with many interference factors, this paper proposes an Automatic Train Control method combining the methods of wavelet packet filtering and iterative learning. First, a train speed filter method based on wavelet packet is designed to obtain better train speed parameters. Then, principal component analysis (PCA) is adopted to reduce the decomposition of velocity data, extract the main train speed information and filter out the clutter. Finally, an adaptive controller is designed by using the iterative learning method. The speed curve tracking control is carried out during the train running, and the parking start position can be determined according to the current speed and displacement, so as to obtain more accurate parking results. The experimental results show that the method combines wavelet, PCA and iterative learning can track the parking curve more accurately." @default.
- W2895839163 created "2018-10-26" @default.
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- W2895839163 date "2018-07-01" @default.
- W2895839163 modified "2023-09-26" @default.
- W2895839163 title "Research on Automatic Train Control Based on Wavelet Package Principal Component Analysis" @default.
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- W2895839163 doi "https://doi.org/10.23919/chicc.2018.8483000" @default.
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