Cooperative Tracking Control of the Multiple-High-Speed Trains System Using a Tunable Artificial Potential Function
Author(s) -
Zhiwu Huang,
Pingping Wang,
Feng Zhou,
Weirong Liu,
Jun Peng
Publication year - 2022
Publication title -
journal of advanced transportation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.577
H-Index - 46
eISSN - 2042-3195
pISSN - 0197-6729
DOI - 10.1155/2022/3639586
Subject(s) - train , range (aeronautics) , tracking (education) , block (permutation group theory) , computer science , control theory (sociology) , function (biology) , potential field , simulation , control (management) , artificial intelligence , engineering , mathematics , aerospace engineering , psychology , pedagogy , geometry , cartography , evolutionary biology , geophysics , geology , biology , geography
It is a challenge to maintain a safe and efficient tracking for multiple high-speed trains under the moving block operational mode. In this paper, a novel cooperative tracking control based on a consensus algorithm and artificial potential field theory is proposed to realize the train tracking within a distance range. A tunable artificial potential function is first designed to dynamically adjust the distance between adjacent high-speed trains with real-time train states. By regulating the parameters of the artificial potential function, the safety distance can be adjusted according to the required tolerance deviation of the actual distance. Under the proposed strategy, each high-speed train operates with the desired speed and tracks the preceding one with an adjustable distance range. Numerical train operational cases are investigated to illustrate the effectiveness of the proposed methods.
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