Network-Based Fractional-Order Control Algorithms for Vehicle Platooning
Fractional-order controllers have been shown to be an effective solution for improving the tracking performance of closed-loop control systems in various engineering applications. However, the use of fractional-order solutions has only been marginally investigated for controlling platoons of vehicle...
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| Format: | Article |
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IEEE
2025-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/11107341/ |
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| author | Omar Hanif Patrick Gruber Aldo Sorniotti Umberto Montanaro |
| author_facet | Omar Hanif Patrick Gruber Aldo Sorniotti Umberto Montanaro |
| author_sort | Omar Hanif |
| collection | DOAJ |
| description | Fractional-order controllers have been shown to be an effective solution for improving the tracking performance of closed-loop control systems in various engineering applications. However, the use of fractional-order solutions has only been marginally investigated for controlling platoons of vehicles. Hence, this paper proposes three novel distributed fractional-order controllers, in which the vehicle platooning control problem of a set of homogeneous followers, characterised by either second- or third-order systems, is reformulated as a consensus control problem. The resulting closed-loop systems are analysed using the root locus approach to determine the region of control gains that ensures asymptotic closed-loop stability. Furthermore, the residual spacing errors to constant leader accelerations and disturbances are computed by analysing the error dynamics in the Laplace domain. The genetic algorithm is then employed for parameter optimisation within the stable region for different scenarios, and numerical analysis supports the theoretical findings and shows reduced tracking error when the fractional-order solutions replace their integer-order counterparts. |
| format | Article |
| id | doaj-art-89c4baf955ce4c949254155a1b78eb37 |
| institution | DOAJ |
| issn | 2169-3536 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj-art-89c4baf955ce4c949254155a1b78eb372025-08-20T03:05:46ZengIEEEIEEE Access2169-35362025-01-011313999214001110.1109/ACCESS.2025.359511611107341Network-Based Fractional-Order Control Algorithms for Vehicle PlatooningOmar Hanif0https://orcid.org/0000-0001-7129-8682Patrick Gruber1https://orcid.org/0000-0003-1030-6655Aldo Sorniotti2https://orcid.org/0000-0002-4848-058XUmberto Montanaro3https://orcid.org/0000-0003-0620-1906Centre for Aerodynamics, Aerospace and Automotive Engineering, School of Engineering, University of Surrey, Guildford, U.K.Centre for Aerodynamics, Aerospace and Automotive Engineering, School of Engineering, University of Surrey, Guildford, U.K.Department of Mechanical and Aerospace Engineering, Politecnico di Torino, Turin, ItalyCentre for Aerodynamics, Aerospace and Automotive Engineering, School of Engineering, University of Surrey, Guildford, U.K.Fractional-order controllers have been shown to be an effective solution for improving the tracking performance of closed-loop control systems in various engineering applications. However, the use of fractional-order solutions has only been marginally investigated for controlling platoons of vehicles. Hence, this paper proposes three novel distributed fractional-order controllers, in which the vehicle platooning control problem of a set of homogeneous followers, characterised by either second- or third-order systems, is reformulated as a consensus control problem. The resulting closed-loop systems are analysed using the root locus approach to determine the region of control gains that ensures asymptotic closed-loop stability. Furthermore, the residual spacing errors to constant leader accelerations and disturbances are computed by analysing the error dynamics in the Laplace domain. The genetic algorithm is then employed for parameter optimisation within the stable region for different scenarios, and numerical analysis supports the theoretical findings and shows reduced tracking error when the fractional-order solutions replace their integer-order counterparts.https://ieeexplore.ieee.org/document/11107341/Vehicle platooningfractional-order controlcooperative control |
| spellingShingle | Omar Hanif Patrick Gruber Aldo Sorniotti Umberto Montanaro Network-Based Fractional-Order Control Algorithms for Vehicle Platooning IEEE Access Vehicle platooning fractional-order control cooperative control |
| title | Network-Based Fractional-Order Control Algorithms for Vehicle Platooning |
| title_full | Network-Based Fractional-Order Control Algorithms for Vehicle Platooning |
| title_fullStr | Network-Based Fractional-Order Control Algorithms for Vehicle Platooning |
| title_full_unstemmed | Network-Based Fractional-Order Control Algorithms for Vehicle Platooning |
| title_short | Network-Based Fractional-Order Control Algorithms for Vehicle Platooning |
| title_sort | network based fractional order control algorithms for vehicle platooning |
| topic | Vehicle platooning fractional-order control cooperative control |
| url | https://ieeexplore.ieee.org/document/11107341/ |
| work_keys_str_mv | AT omarhanif networkbasedfractionalordercontrolalgorithmsforvehicleplatooning AT patrickgruber networkbasedfractionalordercontrolalgorithmsforvehicleplatooning AT aldosorniotti networkbasedfractionalordercontrolalgorithmsforvehicleplatooning AT umbertomontanaro networkbasedfractionalordercontrolalgorithmsforvehicleplatooning |