Title
Robust Control for Dynamic Train Regulation in Fully Automatic Operation System Under Uncertain Wireless Transmissions
Abstract
For enhancing the operation efficiency of the fully automatic operation (FAO) system in the urban rail transit (URT), this paper investigates the robust dynamic train regulation problem with respect to frequent disruptions and imperfect wireless transmissions. To better express the characteristic of the arriving passengers, the fuzzy passenger arrival rate is adopted to address the uncertainty of the passenger flow, and a T-S fuzzy state-space model is established to express the periodical movement of the train traffic in an URT loop line. By considering the possible packet dropout phenomenon during the wireless data transmissions, which may lead to the instability of the train traffic system and degrade the performance of the regulation strategy, a robust real-time train regulation strategy is developed based on the fuzzy predictive control theory, which distinguishes existing studies in that the uncertainty dropout rate is contemplated to address the complexity of the actual operation environment. A sufficient condition for the proposed control law is presented to guarantee that the nominal train schedule is recovered from disturbed situations with a given attenuation level by means of the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$H_{\infty }$ </tex-math></inline-formula> performance index, and meanwhile the optimization of the upper bound on the objective function balancing the service efficiency and control cost is achieved. Numerical simulations based on the Beijing subway loop line 2 are presented for demonstration of the effectiveness of the introduced strategy.
Year
DOI
Venue
2022
10.1109/TITS.2022.3170950
IEEE Transactions on Intelligent Transportation Systems
Keywords
DocType
Volume
Urban transit loop line,automatic train regulation,fuzzy predictive control,uncertain dropout probability
Journal
23
Issue
ISSN
Citations 
11
1524-9050
0
PageRank 
References 
Authors
0.34
23
4
Name
Order
Citations
PageRank
Xi Wang1114.53
Shuai Su2121.52
Yuan Cao37310.39
Xiaoliang Wang400.34