Research of theoretical basis of implementation of intelligent control systems for locomotive traction transmission
The paper presents an analysis of existing automated control systems based on artificial intelligence theory. These systems employ methods such as fuzzy logic, artificial neural networks, and genetic algorithms. The application of these techniques enables the development of more adaptive and effici...
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| Format: | Article |
| Language: | English |
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State University of Infrastructure and Technologies
2025-07-01
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| Series: | Збірник наукових праць Державного університету інфраструктури та технологій: серія "Транспортні системи і технології" |
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| Online Access: | https://tst.duit.in.ua/index.php/tst/article/view/432 |
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| _version_ | 1839642394318864384 |
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| author | Oleksandr Gorobchenko Denys Zaika Sergiy Maliuk Oleksandr Arkhypov Oleksandr Nevedrov |
| author_facet | Oleksandr Gorobchenko Denys Zaika Sergiy Maliuk Oleksandr Arkhypov Oleksandr Nevedrov |
| author_sort | Oleksandr Gorobchenko |
| collection | DOAJ |
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The paper presents an analysis of existing automated control systems based on artificial intelligence theory. These systems employ methods such as fuzzy logic, artificial neural networks, and genetic algorithms. The application of these techniques enables the development of more adaptive and efficient control systems compared to traditional approaches. The main areas of artificial intelligence application in railway transport are identified, particularly in locomotive control systems and optimization of operational modes. The fundamental stages of artificial intelligence-based model development are outlined, including data collection and model training. Key directions for modeling intelligent systems are established. A generalized approach is proposed for the development of an intelligent traction transmission control system for shunting locomotives, taking into account the rolling stock characteristics and operational conditions. For solving control tasks, the use of a production model is proposed, which integrates elements of both logical and network-based approaches. A production model is proposed for solving control tasks.
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| format | Article |
| id | doaj-art-8cdd89f3fff342dc94ea559b1885b51f |
| institution | Matheson Library |
| issn | 2617-9040 2617-9059 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | State University of Infrastructure and Technologies |
| record_format | Article |
| series | Збірник наукових праць Державного університету інфраструктури та технологій: серія "Транспортні системи і технології" |
| spelling | doaj-art-8cdd89f3fff342dc94ea559b1885b51f2025-07-02T09:18:03ZengState University of Infrastructure and TechnologiesЗбірник наукових праць Державного університету інфраструктури та технологій: серія "Транспортні системи і технології"2617-90402617-90592025-07-0145Research of theoretical basis of implementation of intelligent control systems for locomotive traction transmissionOleksandr Gorobchenko0Denys Zaika1Sergiy Maliuk2Oleksandr Arkhypov3Oleksandr Nevedrov4National Transport University, 1, M. Omelianovycha-Pavlenka str., Kyiv, 01010, UkraineNational Transport University, 1, M. Omelianovycha-Pavlenka str., Kyiv, 01010, UkraineNational Transport University, 1, M. Omelianovycha-Pavlenka str., Kyiv, 01010, UkraineNational Transport University, 1, M. Omelianovycha-Pavlenka str., Kyiv, 01010, UkraineNational Transport University, 1, M. Omelianovycha-Pavlenka str., Kyiv, 01010, Ukraine The paper presents an analysis of existing automated control systems based on artificial intelligence theory. These systems employ methods such as fuzzy logic, artificial neural networks, and genetic algorithms. The application of these techniques enables the development of more adaptive and efficient control systems compared to traditional approaches. The main areas of artificial intelligence application in railway transport are identified, particularly in locomotive control systems and optimization of operational modes. The fundamental stages of artificial intelligence-based model development are outlined, including data collection and model training. Key directions for modeling intelligent systems are established. A generalized approach is proposed for the development of an intelligent traction transmission control system for shunting locomotives, taking into account the rolling stock characteristics and operational conditions. For solving control tasks, the use of a production model is proposed, which integrates elements of both logical and network-based approaches. A production model is proposed for solving control tasks. https://tst.duit.in.ua/index.php/tst/article/view/432railway transportrolling stockcontrolartificial intelligenceMamdani methodrisk |
| spellingShingle | Oleksandr Gorobchenko Denys Zaika Sergiy Maliuk Oleksandr Arkhypov Oleksandr Nevedrov Research of theoretical basis of implementation of intelligent control systems for locomotive traction transmission Збірник наукових праць Державного університету інфраструктури та технологій: серія "Транспортні системи і технології" railway transport rolling stock control artificial intelligence Mamdani method risk |
| title | Research of theoretical basis of implementation of intelligent control systems for locomotive traction transmission |
| title_full | Research of theoretical basis of implementation of intelligent control systems for locomotive traction transmission |
| title_fullStr | Research of theoretical basis of implementation of intelligent control systems for locomotive traction transmission |
| title_full_unstemmed | Research of theoretical basis of implementation of intelligent control systems for locomotive traction transmission |
| title_short | Research of theoretical basis of implementation of intelligent control systems for locomotive traction transmission |
| title_sort | research of theoretical basis of implementation of intelligent control systems for locomotive traction transmission |
| topic | railway transport rolling stock control artificial intelligence Mamdani method risk |
| url | https://tst.duit.in.ua/index.php/tst/article/view/432 |
| work_keys_str_mv | AT oleksandrgorobchenko researchoftheoreticalbasisofimplementationofintelligentcontrolsystemsforlocomotivetractiontransmission AT denyszaika researchoftheoreticalbasisofimplementationofintelligentcontrolsystemsforlocomotivetractiontransmission AT sergiymaliuk researchoftheoreticalbasisofimplementationofintelligentcontrolsystemsforlocomotivetractiontransmission AT oleksandrarkhypov researchoftheoreticalbasisofimplementationofintelligentcontrolsystemsforlocomotivetractiontransmission AT oleksandrnevedrov researchoftheoreticalbasisofimplementationofintelligentcontrolsystemsforlocomotivetractiontransmission |