Skip to main content
Log in

Distributed cooperative control of multiple high-speed trains under a moving block system by nonlinear mapping-based feedback

  • Research Paper
  • From CAS & CAE Members
  • Published:
Science China Information Sciences Aims and scope Submit manuscript

Abstract

Although the high-speed railways in China have been greatly advanced in the past decades with respect to expanding networks and increasing speed, a fixed block system, which separates the trains with several stationary track block sections, is utilized to guarantee the safe operation of multiple trains. A moving block system, which enables the moving authority of a high-speed train to be the real-time positioning point of its preceding one (plus some necessary safe redundant distance, of course), is under development to further make full use of the high-speed railway lines and improve the automation level by automatic train operation for high-speed trains. The aim of this paper is to design a distributed cooperative control for high-speed trains under a moving block system by giving a cooperative model with a back-fence communication topology. A nonlinear mapping-based feedback control method together with a rigorous mathematic proof for the global stability and ultimate bound of the closed-loop control systems is proposed. Comparative results are given to demonstrate the effectiveness and advantages of the proposed method.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Dong H R, Gao S G, Ning B. Cooperative control synthesis and stability analysis of multiple trains under moving signaling systems. IEEE Trans Intel Transp Syst, 2016, 17: 2730–2738

    Google Scholar 

  2. Canavan S, Graham D J, Melo P C, et al. Impacts of moving-block signaling on technical efficiency. Trans Res Record-J Transp Res Board, 2015, 2534: 68–74

    Article  Google Scholar 

  3. Wang H F, Tang T, Roberts C, et al. A novel framework for supporting the design of moving block train control system schemes. Proc Institution Mech Eng Part F-J Rail Rapid Transit, 2014, 228: 784–793

    Article  Google Scholar 

  4. Gao S G, Dong H R, Ning B, et al. Cooperative adaptive bidirectional control of a train platoon for efficient utility and string stability. Chin Phys B, 2015, 24: 090506

    Article  Google Scholar 

  5. Chen F, Ren W, Lin Z L. Multi-leader multi-follower coordination with cohesion, dispersion, and containment control via proximity graphs. Sci China Inf Sci, 2017, 60: 110204

    Article  MathSciNet  Google Scholar 

  6. Zhou J L, Yang J Y, Li Z K. Simultaneous attack of a stationary target using multiple missiles: a consensus-based approach. Sci China Inf Sci, 2017, 60: 070205

    Article  MathSciNet  Google Scholar 

  7. Zhang Y, Su Y F. Cooperative output regulation for linear uncertain MIMO multi-agent systems by output feedback. Sci China Inf Sci, 2018, 61: 092206

    Article  MathSciNet  Google Scholar 

  8. Yan X H, Cai B G, Ning B, et al. Online distributed cooperative model predictive control of energy-saving trajectory planning for multiple high-speed train movements. Transp Res Part C-Emerg Technol, 2016, 69: 60–78

    Article  Google Scholar 

  9. Su S, Tang T, Roberts C. A cooperative train control model for energy saving. IEEE Trans Intel Transp Syst, 2015, 16: 622–631

    Article  Google Scholar 

  10. Yang X, Li X, Gao Z Y, et al. A cooperative scheduling model for timetable optimization in subway systems. IEEE Trans Intel Transp Syst, 2013, 14: 438–447

    Article  Google Scholar 

  11. Gao S G, Dong H R, Ning B, et al. Neural adaptive coordination control of multiple trains under bidirectional communication topology. Neural Comput Applic, 2016, 27: 2497–2507

    Article  Google Scholar 

  12. Ge S S, Wang C. Adaptive neural control of uncertain MIMO nonlinear systems. IEEE Trans Neural Netw, 2004, 15: 674–692

    Article  Google Scholar 

  13. Polycarpou M M. Stable adaptive neural control scheme for nonlinear systems. IEEE Trans Autom Control, 1996, 41: 447–451

    Article  MathSciNet  Google Scholar 

  14. Gao S G, Dong H R, Ning B. Neural adaptive dynamic surface control for uncertain strict-feedback nonlinear systems with nonlinear output and virtual feedback errors. Nonlinear Dyn, 2017, 90: 2851–2867

    Article  MathSciNet  Google Scholar 

  15. Gao S G, Dong H R, Chen Y, et al. Approximation-based robust adaptive automatic train control: an approach for actuator saturation. IEEE Trans Intel Transp Syst, 2013, 14: 1733–1742

    Article  Google Scholar 

  16. Cunningham J F, Grossman N. On Young’s inequality. Am Math Mon, 1971, 78: 781–783

    Article  MathSciNet  Google Scholar 

Download references

Acknowledgements

This work was supported by Fundamental Research Funds for Central Universities (Grant No. 2018JBM077), National Natural Science Foundation of China (Grant Nos. 61790573, 61703033) and State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University (Grant No. RCS2018ZT013).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Hairong Dong.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Ning, B., Dong, H., Gao, S. et al. Distributed cooperative control of multiple high-speed trains under a moving block system by nonlinear mapping-based feedback. Sci. China Inf. Sci. 61, 120202 (2018). https://doi.org/10.1007/s11432-018-9563-y

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s11432-018-9563-y

Keywords

Navigation