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Predictive Function Control for Communication-Based Train Control (CBTC) Systems
Author(s) -
Bing Bu,
Jingwei Yang,
Shuhuan Wen,
Li Zhu
Publication year - 2013
Publication title -
international journal of advanced robotic systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.394
H-Index - 46
eISSN - 1729-8814
pISSN - 1729-8806
DOI - 10.5772/53514
Subject(s) - computer science , train , control theory (sociology) , robustness (evolution) , network packet , model predictive control , linear matrix inequality , control system , controller (irrigation) , wireless , control (management) , mathematical optimization , engineering , computer network , telecommunications , mathematics , biochemistry , chemistry , agronomy , cartography , artificial intelligence , biology , electrical engineering , gene , geography
In Communication-Based Train Control (CBTC) systems, random transmission delays and packet drops are inevitable in the wireless networks, which could result in unnecessary traction, brakes or even emergency brakes of trains, losses of line capacity and passenger dissatisfaction. This paper applies predictive function control technology with a mixed H2/∞ control approach to improve the control performances. The controller is in the state feedback form and satisfies the requirement of quadratic input and state constraints. A linear matrix inequality (LMI) approach is developed to solve the control problem. The proposed method attenuates disturbances by incorporating H2/∞ into the control scheme. The control command from the automatic train operation (ATO) is included in the reward function to optimize the train's running profile. The influence of transmission delays and packet drops is alleviated through improving the performances of the controller. Simulation results show that the method is effective to improve the performances and robustness of CBTC systems

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