Model-free adaptive robust control method for high-speed trains

Aiming at the robustness issue in high-speed trains (HSTs) operation control, this article proposes a model-free adaptive control (MFAC) scheme to suppress disturbance. Firstly, the dynamic linearization data model of train system under the action of measurement disturbance is given, and the Kalman filter (KF) based on this model is derived under the minimum variance estimation criterion. Then, according to the KF, an anti-interference MFAC scheme is designed. This scheme only needs the input and output data of the controlled system to realize the MFAC of the train under strong disturbance. Finally, the simulation experiment of CRH380A HSTs is carried out and compared with the traditional MFAC and the MFAC with attenuation factor. The proposed control algorithm can effectively suppress the measurement disturbance, and obtain smaller tracking error and larger signal to noise ratio with better applicability.

• Record URL:
  • https://doi.org/10.1093/tse/tdad013
• Supplemental Notes:
  • © The Authors 2023. Published by Oxford University Press on behalf of Central South University Press.
• Authors:
  • Li, Zhongqi
  • 0000-0002-7910-7278
  • Zhou, Liang
  • 0000-0002-6017-4649
  • Yang, Hui
  • Yan, Yue
• Publication Date: 2024-2

Language

• English

Media Info

• Media Type: Digital/other
• Features: Figures; References; Tables;
• Pagination: tdad013
• Serial:
  • Transportation Safety and Environment
  • Volume: 6
  • Issue Number: 1
  • Publisher: Oxford University Press
  • EISSN: 2631-4428
  • Serial URL: https://academic.oup.com/tse
• Publication flags:

  Open Access (libre)

Subject/Index Terms

• TRT Terms: Adaptive control; Automatic tracking; Automatic train operation; Curved track; High speed rail; Kalman filtering
• Subject Areas: Operations and Traffic Management; Railroads; Vehicles and Equipment;

Filing Info

• Accession Number: 01914165
• Record Type: Publication
• Files: TRIS
• Created Date: Apr 10 2024 5:15PM