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Adaptive Iterative Learning Control Based High Speed Train Operation Tracking Under Iteration‐Varying Parameter and Measurement Noise
Author(s) -
Li Zhenxuan,
Hou Zhongsheng
Publication year - 2015
Publication title -
asian journal of control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.769
H-Index - 53
eISSN - 1934-6093
pISSN - 1561-8625
DOI - 10.1002/asjc.1093
Subject(s) - iterative learning control , noise (video) , control theory (sociology) , tracking (education) , iterative method , computer science , control (management) , algorithm , artificial intelligence , psychology , pedagogy , image (mathematics)
Abstract The iterative learning control (ILC)‐based automatic train operation is proposed to address a high speed train (HST) tracking problem with consideration of the iteration‐varying operation condition. The iteration‐varying operation condition considered in this paper is the air resistance coefficient of an HST, which may be completely different at two consecutive operation processes due to different weather conditions. In addition, to alleviate the effect of measurement noise, the proposed method is modified further. The effectiveness of these two proposed methods are verified by theoretical analysis and numerical simulation.