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Virtual Parameter Learning-Based Adaptive Control for Protective Automatic Train Operation

  • Published:2021-12 Issue:12 Volume:22 Page:7943-7954
  • ISSN:1524-9050
  • Container-title:IEEE Transactions on Intelligent Transportation Systems
  • language:
  • Short-container-title:IEEE Trans. Intell. Transport. Syst.

Author:

Yuan ZhimingORCID,Yan LuORCID,Gao YingORCID,Zhang Tao,Gao ShigenORCID

Funder

National Natural Science Foundation of China

Beijing Natural Science Foundation

National Research Center of Railway Intelligent Transport System Engineering Technology Founding

State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Science Applications,Mechanical Engineering,Automotive Engineering

Cited by 9 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Deterministic reinforcement learning for optimized formation control of virtually-coupled trains via performance index monitor;Expert Systems with Applications;2024-03

2. Speed Tracking and Anti-Slip Control for Heavy Freight Trains Considering the Conicity of the Wheel;Transportation Research Record: Journal of the Transportation Research Board;2024-01-08

3. A Strategy Based on LSTM Controller With Adaptive Proportional Compensation for High-Speed Train Operation Control;IEEE Transactions on Intelligent Transportation Systems;2024

4. History Makes the Future: Iterative Learning Control for High-Speed Trains;IEEE Intelligent Transportation Systems Magazine;2024-01

5. Adaptive Backstepping Sliding Mode Control of High-speed Train Based on Fuzzy Regulation;2023 5th International Conference on Industrial Artificial Intelligence (IAI);2023-08-21
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