Multi-Agent Consistent Formation Control Operation Optimization for High-Speed Trains
High-speed trains delay may happen due to the complicated and erratic operating circumstances of railway lines. In this paper, the problems of delayed recovery in high-speed train operations and the rapid acquisition of optimal trajectory for train offline operations are investigated. Firstly, takin...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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IEEE
2023-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10352147/ |
| _version_ | 1797376315312046080 |
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| author | Huiqin Pei Zhuyuan Lan |
| author_facet | Huiqin Pei Zhuyuan Lan |
| author_sort | Huiqin Pei |
| collection | DOAJ |
| description | High-speed trains delay may happen due to the complicated and erratic operating circumstances of railway lines. In this paper, the problems of delayed recovery in high-speed train operations and the rapid acquisition of optimal trajectory for train offline operations are investigated. Firstly, taking on-time performance and energy saving as optimization objectives, an information communication topology model of train group is established. Then, a variable-parameter multi-objective particle swarm optimization algorithm is proposed to determine the best trajectory for train offline operation. The algorithm prevents decision variables from falling into a local optimum and effectively increases the speed of the overall search for an optimum. Secondly, consider the delay phenomenon in the dynamic process of online train operation, the idea of multi-agent consistent formation control is introduced, and an online train operation controller is designed to provide feedback regulation of the speed and position of trains deviating from the offline operation trajectory. The stability of train operation control system is demonstrated by Lyapunov’s method. The controller can improve the immunity of disturbance and delay recovery for train operation. Finally, using actual data from the Wuhan to Changsha South line, the validity of the proposed theoretical results is further verified. |
| first_indexed | 2024-03-08T19:36:46Z |
| format | Article |
| id | doaj.art-da07ad3a19ce445891570ded34921f17 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-03-08T19:36:46Z |
| publishDate | 2023-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-da07ad3a19ce445891570ded34921f172023-12-26T00:09:33ZengIEEEIEEE Access2169-35362023-01-011113920113921010.1109/ACCESS.2023.334122510352147Multi-Agent Consistent Formation Control Operation Optimization for High-Speed TrainsHuiqin Pei0https://orcid.org/0000-0003-4489-4803Zhuyuan Lan1School of Electrical and Automation Engineering, East China Jiaotong University, Nanchang, ChinaSchool of Electrical and Automation Engineering, East China Jiaotong University, Nanchang, ChinaHigh-speed trains delay may happen due to the complicated and erratic operating circumstances of railway lines. In this paper, the problems of delayed recovery in high-speed train operations and the rapid acquisition of optimal trajectory for train offline operations are investigated. Firstly, taking on-time performance and energy saving as optimization objectives, an information communication topology model of train group is established. Then, a variable-parameter multi-objective particle swarm optimization algorithm is proposed to determine the best trajectory for train offline operation. The algorithm prevents decision variables from falling into a local optimum and effectively increases the speed of the overall search for an optimum. Secondly, consider the delay phenomenon in the dynamic process of online train operation, the idea of multi-agent consistent formation control is introduced, and an online train operation controller is designed to provide feedback regulation of the speed and position of trains deviating from the offline operation trajectory. The stability of train operation control system is demonstrated by Lyapunov’s method. The controller can improve the immunity of disturbance and delay recovery for train operation. Finally, using actual data from the Wuhan to Changsha South line, the validity of the proposed theoretical results is further verified.https://ieeexplore.ieee.org/document/10352147/High-speed trainsmulti-objective particle swarm optimization algorithmconsistent formation controloperation optimization |
| spellingShingle | Huiqin Pei Zhuyuan Lan Multi-Agent Consistent Formation Control Operation Optimization for High-Speed Trains IEEE Access High-speed trains multi-objective particle swarm optimization algorithm consistent formation control operation optimization |
| title | Multi-Agent Consistent Formation Control Operation Optimization for High-Speed Trains |
| title_full | Multi-Agent Consistent Formation Control Operation Optimization for High-Speed Trains |
| title_fullStr | Multi-Agent Consistent Formation Control Operation Optimization for High-Speed Trains |
| title_full_unstemmed | Multi-Agent Consistent Formation Control Operation Optimization for High-Speed Trains |
| title_short | Multi-Agent Consistent Formation Control Operation Optimization for High-Speed Trains |
| title_sort | multi agent consistent formation control operation optimization for high speed trains |
| topic | High-speed trains multi-objective particle swarm optimization algorithm consistent formation control operation optimization |
| url | https://ieeexplore.ieee.org/document/10352147/ |
| work_keys_str_mv | AT huiqinpei multiagentconsistentformationcontroloperationoptimizationforhighspeedtrains AT zhuyuanlan multiagentconsistentformationcontroloperationoptimizationforhighspeedtrains |