Event-triggered predictive control of high-speed trains under virtual coupling

To address the control problem of high-speed trains operating under virtual coupling in actual communication environments, an event-triggered multi-trains cooperative tracking predictive control method is proposed considering the limited available resources of the system. Firstly, a multi-trains tra...

Full description

Saved in:
Bibliographic Details
Main Authors: Jianliang Xu, Zhen Sui, Xiaohua Wei, Feng Xu
Format: Article
Language:English
Published: Taylor & Francis Group 2025-10-01
Series:Automatika
Subjects:
Online Access:https://www.tandfonline.com/doi/10.1080/00051144.2025.2526146
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1849706680387895296
author Jianliang Xu
Zhen Sui
Xiaohua Wei
Feng Xu
author_facet Jianliang Xu
Zhen Sui
Xiaohua Wei
Feng Xu
author_sort Jianliang Xu
collection DOAJ
description To address the control problem of high-speed trains operating under virtual coupling in actual communication environments, an event-triggered multi-trains cooperative tracking predictive control method is proposed considering the limited available resources of the system. Firstly, a multi-trains tracking model is established based on train dynamic equations, and the optimal tracking control problem is formulated according to the train running mechanism. Secondly, addressing the low computational efficiency and resource wastage in model predictive control, an event-triggered mechanism is introduced to enhance system real-time performance by incorporating judgment conditions during optimization problem-solving. Furthermore, the feasibility and stability of this control method are validated through theoretical analysis. Simulation results indicate that the speed and distance root-mean-square errors of the multi-trains obtained by the proposed control method are 6.25×10−4 and 1.8×10−4 respectively, indicating that the proposed method has good control and tracking performance. With the increase of trigger parameters, the number of triggers is reduced from 2500 to 799, and the calculation time is also reduced by about 51.7%, which further improves the resource utilization of the control system. It can be seen that the control method in this paper can well solve the multi-trains tracking control problem under the condition of resource limitation.
format Article
id doaj-art-9dbc7777696a47bd9f993ff6010b7170
institution DOAJ
issn 0005-1144
1848-3380
language English
publishDate 2025-10-01
publisher Taylor & Francis Group
record_format Article
series Automatika
spelling doaj-art-9dbc7777696a47bd9f993ff6010b71702025-08-20T03:16:07ZengTaylor & Francis GroupAutomatika0005-11441848-33802025-10-01664112110.1080/00051144.2025.2526146Event-triggered predictive control of high-speed trains under virtual couplingJianliang Xu0Zhen Sui1Xiaohua Wei2Feng Xu3School of Mechanical Engineering, Quzhou College and Technology, Quzhou, People’s Republic of China College of Communication Engineering, Jilin University, Changchun, People’s Republic of ChinaSchool of Mechanical Engineering, Quzhou College and Technology, Quzhou, People’s Republic of China School of Mechanical Engineering, Quzhou College and Technology, Quzhou, People’s Republic of China To address the control problem of high-speed trains operating under virtual coupling in actual communication environments, an event-triggered multi-trains cooperative tracking predictive control method is proposed considering the limited available resources of the system. Firstly, a multi-trains tracking model is established based on train dynamic equations, and the optimal tracking control problem is formulated according to the train running mechanism. Secondly, addressing the low computational efficiency and resource wastage in model predictive control, an event-triggered mechanism is introduced to enhance system real-time performance by incorporating judgment conditions during optimization problem-solving. Furthermore, the feasibility and stability of this control method are validated through theoretical analysis. Simulation results indicate that the speed and distance root-mean-square errors of the multi-trains obtained by the proposed control method are 6.25×10−4 and 1.8×10−4 respectively, indicating that the proposed method has good control and tracking performance. With the increase of trigger parameters, the number of triggers is reduced from 2500 to 799, and the calculation time is also reduced by about 51.7%, which further improves the resource utilization of the control system. It can be seen that the control method in this paper can well solve the multi-trains tracking control problem under the condition of resource limitation.https://www.tandfonline.com/doi/10.1080/00051144.2025.2526146Virtual coupling technologymulti-trains cooperative controlevent triggering mechanismmodel predictive controlstability
spellingShingle Jianliang Xu
Zhen Sui
Xiaohua Wei
Feng Xu
Event-triggered predictive control of high-speed trains under virtual coupling
Automatika
Virtual coupling technology
multi-trains cooperative control
event triggering mechanism
model predictive control
stability
title Event-triggered predictive control of high-speed trains under virtual coupling
title_full Event-triggered predictive control of high-speed trains under virtual coupling
title_fullStr Event-triggered predictive control of high-speed trains under virtual coupling
title_full_unstemmed Event-triggered predictive control of high-speed trains under virtual coupling
title_short Event-triggered predictive control of high-speed trains under virtual coupling
title_sort event triggered predictive control of high speed trains under virtual coupling
topic Virtual coupling technology
multi-trains cooperative control
event triggering mechanism
model predictive control
stability
url https://www.tandfonline.com/doi/10.1080/00051144.2025.2526146
work_keys_str_mv AT jianliangxu eventtriggeredpredictivecontrolofhighspeedtrainsundervirtualcoupling
AT zhensui eventtriggeredpredictivecontrolofhighspeedtrainsundervirtualcoupling
AT xiaohuawei eventtriggeredpredictivecontrolofhighspeedtrainsundervirtualcoupling
AT fengxu eventtriggeredpredictivecontrolofhighspeedtrainsundervirtualcoupling