Optimal control of heavy haul train based on approximate dynamic programming
This research investigates the optimal control problem of heavy haul train for the minimization of longitudinal forces. As the heavy haul train is much heavier and longer than ordinary train, the in-train forces should be carefully manipulated to reduce the train’s maintenance cost and, most importa...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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SAGE Publishing
2017-04-01
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| Series: | Advances in Mechanical Engineering |
| Online Access: | https://doi.org/10.1177/1687814017698110 |
| _version_ | 1818693377919549440 |
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| author | Xi Wang Tao Tang Hui He |
| author_facet | Xi Wang Tao Tang Hui He |
| author_sort | Xi Wang |
| collection | DOAJ |
| description | This research investigates the optimal control problem of heavy haul train for the minimization of longitudinal forces. As the heavy haul train is much heavier and longer than ordinary train, the in-train forces should be carefully manipulated to reduce the train’s maintenance cost and, most importantly, to ensure operation safety. Specifically, the limitations of pneumatically controlled braking system increase the need for the optimal control strategy to accounting for future grades, speed restrictions and uncertain disturbances. In this article, the stochastic dynamic programming model is adopt to set up a rigorous mathematical formulation for heavy haul train control, and approximate dynamic programming algorithm with lookup table representation is introduced to find the optimal solution of the considered problem. By handling the existed uncertainties in a mathematical way, the post-decision state variable is utilized to represent the state of the heavy haul train after we have made a control decision but before any exogenous information has arrived. Finally, the computational results demonstrate the effectiveness and performance of the proposed model and algorithm. |
| first_indexed | 2024-12-17T13:12:43Z |
| format | Article |
| id | doaj.art-23d2304980714ed7a960ad05e8b8afcf |
| institution | Directory Open Access Journal |
| issn | 1687-8140 |
| language | English |
| last_indexed | 2024-12-17T13:12:43Z |
| publishDate | 2017-04-01 |
| publisher | SAGE Publishing |
| record_format | Article |
| series | Advances in Mechanical Engineering |
| spelling | doaj.art-23d2304980714ed7a960ad05e8b8afcf2022-12-21T21:47:05ZengSAGE PublishingAdvances in Mechanical Engineering1687-81402017-04-01910.1177/1687814017698110Optimal control of heavy haul train based on approximate dynamic programmingXi Wang0Tao Tang1Hui He2National Engineering Research Center of Rail Transportation Operation and Control System, Beijing Jiaotong University, Beijing, ChinaState Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing, ChinaState Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing, ChinaThis research investigates the optimal control problem of heavy haul train for the minimization of longitudinal forces. As the heavy haul train is much heavier and longer than ordinary train, the in-train forces should be carefully manipulated to reduce the train’s maintenance cost and, most importantly, to ensure operation safety. Specifically, the limitations of pneumatically controlled braking system increase the need for the optimal control strategy to accounting for future grades, speed restrictions and uncertain disturbances. In this article, the stochastic dynamic programming model is adopt to set up a rigorous mathematical formulation for heavy haul train control, and approximate dynamic programming algorithm with lookup table representation is introduced to find the optimal solution of the considered problem. By handling the existed uncertainties in a mathematical way, the post-decision state variable is utilized to represent the state of the heavy haul train after we have made a control decision but before any exogenous information has arrived. Finally, the computational results demonstrate the effectiveness and performance of the proposed model and algorithm.https://doi.org/10.1177/1687814017698110 |
| spellingShingle | Xi Wang Tao Tang Hui He Optimal control of heavy haul train based on approximate dynamic programming Advances in Mechanical Engineering |
| title | Optimal control of heavy haul train based on approximate dynamic programming |
| title_full | Optimal control of heavy haul train based on approximate dynamic programming |
| title_fullStr | Optimal control of heavy haul train based on approximate dynamic programming |
| title_full_unstemmed | Optimal control of heavy haul train based on approximate dynamic programming |
| title_short | Optimal control of heavy haul train based on approximate dynamic programming |
| title_sort | optimal control of heavy haul train based on approximate dynamic programming |
| url | https://doi.org/10.1177/1687814017698110 |
| work_keys_str_mv | AT xiwang optimalcontrolofheavyhaultrainbasedonapproximatedynamicprogramming AT taotang optimalcontrolofheavyhaultrainbasedonapproximatedynamicprogramming AT huihe optimalcontrolofheavyhaultrainbasedonapproximatedynamicprogramming |