skip to main content
10.1145/3687488.3687526acmotherconferencesArticle/Chapter ViewAbstractPublication PagesiccirConference Proceedingsconference-collections
research-article

Distributed Coordinative Control for Virtually Coupled Sky Train Set via A Novel Finite-Time Sliding Mode Control Approach

Published: 18 November 2024 Publication History

Abstract

Virtual coupling (VC) represents a cutting-edge railway technology that enables unit trains to operate closely together as a coordinated unit without physical connections, enhancing efficiency and capacity on railway networks. Recently, a novel rail transit method, sky trains, has been gradually developing with technological and infrastructural advancements. This paper introduces the concept of virtually coupled sky train set (VCSTS) and proposes a finite-time coordinative control method for VCSTS that addresses state constraints and uncertain parameters. First, a VCSTS train-following model that accounts for uncertain resistances and unknown disturbances is constructed. Then, by combining finite-time control and barrier function theory, a novel distributed coordinative control strategy is designed, which can realize finite-time convergence as well as manage uncertain parameters and state constraints. Using Lyapunov theory, the finite-time convergence of the designed control strategy is rigorously proved. Ultimately, simulations are performed to validate the theoretical findings.

References

[1]
S. Su, X. Wang, T. Tang, G. Wang, and Y. Cao, “Energy efficient operation by cooperative control among trains: A multi agent reinforcement learning approach,” Control Engineering Practice, vol.116, p. 104901,2021.
[2]
X. Wang, A. D'Ariano, S. Su, and T. Tang, “Cooperative train control during the power supply shortage in metro system: A multi-agent reinforcement learning approach,” Transportation Research Part B: Methodological, vol.170, pp.244–278,2023.
[3]
S. Su, Q. Zhu, J. Liu, T. Tang, Q. Wei, and Y. Cao, “A data-driven iterative learning approach for optimizing the train control strategy,” IEEE Transaction son Industrial Informatics, vol.19, no.7, pp.7885–7893,2023.
[4]
Z. Wang, T. Tang, S. Su, A. D'Ariano, T. Bosi, and B. Su,“ Optimizing train-to-train rescue and rescheduling in metro systems,” IEEE Transactions on Intelligent Transportation Systems,2024.
[5]
B. Su, A. D'Ariano, S. Su, X. Wang, and T. Tang, “Integrated train timetabling and rolling stock rescheduling for a disturbed metro system: A hybrid deep reinforcement learning and adaptive large neighborhood search approach,” Computers &Industrial Engineering, vol.186, p.109742,2023.
[6]
Q. Wu, X. Ge, Q.-L. Han, and Y. Liu, “Railway virtual coupling: A survey of emerging control techniques,” IEEE Transactions onIntelligentVehicles,2023.
[7]
Q. Wu, X. Ge, S. Zhu, C. Cole, and M. Spiryagin, “Physical coupling and decoupling of railway trains at cruising speeds: train control and dynamics,” International Journal of Rail Transportation, vol.12, no.2, pp.217–232,2024.
[8]
Q. Wu, X. Ge, Q.-L. Han, B. Wang, H. Wu, C. Cole, and M. Spiryagin, “Dynamics and control simulation of railway virtual coupling,” Vehicle System Dynamics, vol. 6l, no. 9, pp2292-2316, 2023.
[9]
S. Xiao, X. Ge, Q. Wu, and L. Ding, “Co-design of bandwidth aware communication scheduler and cruise controller for multiple high-speed trains,", lEEE Transactions on Vehicular Technology, vol.73, no.4, pp.4993-5004, 2024.
[10]
S. Xiao, X. Ge, and Q. Wu, “Attack-resilient distributed co-operative control of virtually coupled high-speed trains via topology reconfiguration, IEEE/CAA Journal of Automatica Sinica, vol.11, no.4, pp.1066-1068, 2024.
[11]
S. Su, W. Liu, Q. Zhu, R. Li, T. Tang, and J. Lv, “A cooperative collision-avoidance control methodology for virtual coupling trains,” Accident Analysis & Prevention, vol. 173, p. 106703, 2022.
[12]
S. Su, J. She, K. Li, X. Wang, and Y. Zhou, “A nonlinear safety equilibrium spacing-based model predictive control for virtually coupled train set over gradient terrains,” IEEE Transactions on transportation electrification, vol. 8, no. 2, pp. 2810–2824, 2021.
[13]
S. Su, J. She, D. Wang, S. Gong, and Y. Zhou, “A stabilized virtual coupling scheme for a train set with heterogeneous braking dynamics capability,” Transportation Research Part C: Emerging Technologies, vol. 146, p. 103947, 2023.
[14]
L. Zhu, D. Huang, X. Li, and Q. Wang, “Cooperative operation control of virtual coupling high-speed trains with input saturation and full-state constraints,” IEEE Transactions on Automation Science and Engineering, 2023.
[15]
Y. Liu, Y. Zhou, S. Su, J. Xun, and T. Tang, “Control strategy for stable formation of high-speed virtually coupled trains with disturbances and delays,” Computer-Aided Civil and Infrastructure Engineering, vol. 38, no. 5, pp. 621–639, 2023.
[16]
X. Ge, Q. Wu, Q.-L. Han, and X.-M. Zhang, “Resilient virtual coupling control of automatic train convoys with intermittent communications,” IEEE Transactions on Vehicular Technology, 2023.
[17]
X. Luo, T. Tang, J. Yin, and H. Liu, “A robust mpc approach with controller tuning for close following operation of virtually coupled train set,” Transportation Research Part C: Emerging Technologies, vol. 151, p. 104116, 2023.
[18]
Q. Wu, X. Ge, S. Zhu, C. Cole, and M. Spiryagin, “A time headway control scheme for virtually coupled heavy haul freight trains,” Journal of Dynamic Systems, Measurement, and Control, vol. 146, no. 4, 2024.
[19]
S. Su, D. Wang, Y. Cao, Y. Zhou, and T. Tang, “Adaptive fault tolerant fixed-time cruise control for virtually coupled train set,” Transportation Research Part C: Emerging Technologies, vol. 156, p. 104348, 2023.
[20]
Z. Zhang, H. Song, H. Wang, X. Wang, and H. Dong, “Cooperative multi-scenario departure control for virtual coupling trains: A fixed-time approach,” IEEE Transactions on Vehicular Technology, vol. 70, no. 9, pp. 8545–8555, 2021.
[21]
D. Wang, S. Su, L. Han, and D. Li, “Finite-time distributed adaptive coordinated control for multiple traction units of high speed trains,” IEEE Transactions on Intelligent Transportation Systems, 2024.
[22]
D. Wang and Y. Cao, “Adaptive finite-time sliding mode control of virtually coupled train set with state constraints,” in 2022 IEEE 25th International Conference on Intelligent Transportation Systems (ITSC). IEEE, 2022, pp. 1778–1783.
[23]
S. Su, L. Han, and S. Li, “Finite-time event-triggered consensus control for high-speed train with gradient resistance,” Journal of the Franklin Institute, vol. 359, no. 2, pp. 1144–1175, 2022
[24]
S. Su, X. Wang, Y. Cao, and J. Yin, “An energy-efficient train operation approach by integrating the metro timetabling and eco-driving,” IEEE Transactions on Intelligent Transportation Systems, vol. 21, no. 10, pp. 4252–4268, 2019.
[25]
X. Zhao, T. Tang, D. Wang, and S. Su, “Distributed fixed-time formation control for heavy haul trains based on sliding mode control,” Physica A: Statistical Mechanics and its Applications, vol. 633, p. 129428, 2024.
[26]
Y. Wang, Y. Song, M. Krstic, and C. Wen, “Fault-tolerant finite time consensus for multiple uncertain nonlinear mechanical systems under single-way directed communication interactions and actuation failures,” Automatica, vol. 63, pp. 374–383, 2016.

Index Terms

  1. Distributed Coordinative Control for Virtually Coupled Sky Train Set via A Novel Finite-Time Sliding Mode Control Approach

    Recommendations

    Comments

    Information & Contributors

    Information

    Published In

    cover image ACM Other conferences
    ICCIR '24: Proceedings of the 2024 4th International Conference on Control and Intelligent Robotics
    June 2024
    399 pages
    ISBN:9798400709937
    DOI:10.1145/3687488
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

    Publisher

    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 18 November 2024

    Check for updates

    Author Tags

    1. Virtually coupled sky train set
    2. coordinative control
    3. state constraint
    4. uncertain parameters

    Qualifiers

    • Research-article

    Conference

    ICCIR 2024

    Acceptance Rates

    Overall Acceptance Rate 131 of 239 submissions, 55%

    Contributors

    Other Metrics

    Bibliometrics & Citations

    Bibliometrics

    Article Metrics

    • 0
      Total Citations
    • 23
      Total Downloads
    • Downloads (Last 12 months)23
    • Downloads (Last 6 weeks)9
    Reflects downloads up to 03 Mar 2025

    Other Metrics

    Citations

    View Options

    Login options

    View options

    PDF

    View or Download as a PDF file.

    PDF

    eReader

    View online with eReader.

    eReader

    Full Text

    View this article in Full Text.

    Full Text

    HTML Format

    View this article in HTML Format.

    HTML Format

    Figures

    Tables

    Media

    Share

    Share

    Share this Publication link

    Share on social media