A Robust Model Predictive Control for Virtual Coupling in Train Sets
In recent decades, the demand for rail transport has been growing steadily and faces a double problem. Not only must the transport capacity be increased, but also a more flexible service is needed to meet the real demand. Both objectives can be achieved through virtual coupling (VC), which is an evo...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-12-01
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| Series: | Actuators |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-0825/11/12/372 |
| _version_ | 1797462016075497472 |
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| author | Jesus Felez Miguel Angel Vaquero-Serrano Juan de Dios Sanz |
| author_facet | Jesus Felez Miguel Angel Vaquero-Serrano Juan de Dios Sanz |
| author_sort | Jesus Felez |
| collection | DOAJ |
| description | In recent decades, the demand for rail transport has been growing steadily and faces a double problem. Not only must the transport capacity be increased, but also a more flexible service is needed to meet the real demand. Both objectives can be achieved through virtual coupling (VC), which is an evolution of the current moving block systems. Trains under VC can run much closer together, forming what is called a virtually coupled train set (VCTS). In this paper, we propose an approach in which virtual coupling is implemented via model predictive control (MPC). For this purpose, we define a robust controller that can predict, based on a dynamic model of the train, the state of the system at later moments of time and make the appropriate control decisions. A robust MPC (RMPC) is obtained by introducing two uncertain variables. The first uncertain variable is added to the acceleration equation of the dynamic model, while the second uncertain variable is used to define the uncertainty in the train positioning. To test the RMPC for virtual coupling, two simulation cases are performed for a metro line, analysing the influence of both the uncertainties. In all cases, the results obtained show a safer operation of the virtual coupling without significantly affecting the service. |
| first_indexed | 2024-03-09T17:28:26Z |
| format | Article |
| id | doaj.art-e9dcd11b4d604e2f86e6d563a34a5fe4 |
| institution | Directory Open Access Journal |
| issn | 2076-0825 |
| language | English |
| last_indexed | 2024-03-09T17:28:26Z |
| publishDate | 2022-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Actuators |
| spelling | doaj.art-e9dcd11b4d604e2f86e6d563a34a5fe42023-11-24T12:35:25ZengMDPI AGActuators2076-08252022-12-01111237210.3390/act11120372A Robust Model Predictive Control for Virtual Coupling in Train SetsJesus Felez0Miguel Angel Vaquero-Serrano1Juan de Dios Sanz2Mechanical Engineering Department, Universidad Politécnica de Madrid, Jose Gutierrez Abascal 2, 28006 Madrid, SpainMechanical Engineering Department, Universidad Politécnica de Madrid, Jose Gutierrez Abascal 2, 28006 Madrid, SpainMechanical Engineering Department, Universidad Politécnica de Madrid, Jose Gutierrez Abascal 2, 28006 Madrid, SpainIn recent decades, the demand for rail transport has been growing steadily and faces a double problem. Not only must the transport capacity be increased, but also a more flexible service is needed to meet the real demand. Both objectives can be achieved through virtual coupling (VC), which is an evolution of the current moving block systems. Trains under VC can run much closer together, forming what is called a virtually coupled train set (VCTS). In this paper, we propose an approach in which virtual coupling is implemented via model predictive control (MPC). For this purpose, we define a robust controller that can predict, based on a dynamic model of the train, the state of the system at later moments of time and make the appropriate control decisions. A robust MPC (RMPC) is obtained by introducing two uncertain variables. The first uncertain variable is added to the acceleration equation of the dynamic model, while the second uncertain variable is used to define the uncertainty in the train positioning. To test the RMPC for virtual coupling, two simulation cases are performed for a metro line, analysing the influence of both the uncertainties. In all cases, the results obtained show a safer operation of the virtual coupling without significantly affecting the service.https://www.mdpi.com/2076-0825/11/12/372railwayvirtual couplingoptimal controlmodel predictive controlrobust MPC |
| spellingShingle | Jesus Felez Miguel Angel Vaquero-Serrano Juan de Dios Sanz A Robust Model Predictive Control for Virtual Coupling in Train Sets Actuators railway virtual coupling optimal control model predictive control robust MPC |
| title | A Robust Model Predictive Control for Virtual Coupling in Train Sets |
| title_full | A Robust Model Predictive Control for Virtual Coupling in Train Sets |
| title_fullStr | A Robust Model Predictive Control for Virtual Coupling in Train Sets |
| title_full_unstemmed | A Robust Model Predictive Control for Virtual Coupling in Train Sets |
| title_short | A Robust Model Predictive Control for Virtual Coupling in Train Sets |
| title_sort | robust model predictive control for virtual coupling in train sets |
| topic | railway virtual coupling optimal control model predictive control robust MPC |
| url | https://www.mdpi.com/2076-0825/11/12/372 |
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