Fractional Order Sliding Mode Control With GA Tuning for a UAV Quadrotor
Fractional order calculus (FOC) uses arbitrary order operations in differentiation and integration. Previously, the absence of methods to solve fractional differential equations limited the application of fractional order calculus. However, with the development of new methods, FOC is now applicable...
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IEEE
2024-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/10769462/ |
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| author | Najib Alabsari Abdul-Wahid A. Saif Sami El-Ferik Salih Duffuaa Nabil Derbel |
| author_facet | Najib Alabsari Abdul-Wahid A. Saif Sami El-Ferik Salih Duffuaa Nabil Derbel |
| author_sort | Najib Alabsari |
| collection | DOAJ |
| description | Fractional order calculus (FOC) uses arbitrary order operations in differentiation and integration. Previously, the absence of methods to solve fractional differential equations limited the application of fractional order calculus. However, with the development of new methods, FOC is now applicable in various fields and has been utilized to enhance control system performance in traditional techniques. FOC is used in this study to develop a new fractional structure for the sliding mode control approach that offers improved performance and more robustness to external disturbances. The fractional order sliding mode control (FOSMC) strategy is designed using a Lyapunov-based sliding condition to ensure system stability. To enhance performance, genetic algorithms are used to adjust the fractional orders and controller parameters. The proposed fractional sliding mode control system is applied on an unmanned aerial vehicle system affected by external disturbances and then it is compared with a conventional integer order sliding mode control (IOSMC) system. Simulation results have proved the efficiency of the proposed fractional order controller where it outperforms the conventional sliding mode controller in terms of better transient dynamics and more robustness to external disturbances. |
| format | Article |
| id | doaj-art-e464fe3131644db7b79040293ce8ac5a |
| institution | OA Journals |
| issn | 2169-3536 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj-art-e464fe3131644db7b79040293ce8ac5a2025-08-20T02:33:48ZengIEEEIEEE Access2169-35362024-01-011217920417921810.1109/ACCESS.2024.350710010769462Fractional Order Sliding Mode Control With GA Tuning for a UAV QuadrotorNajib Alabsari0https://orcid.org/0009-0000-3512-2268Abdul-Wahid A. Saif1https://orcid.org/0000-0003-2969-1581Sami El-Ferik2https://orcid.org/0000-0001-5648-4786Salih Duffuaa3https://orcid.org/0000-0001-6128-9184Nabil Derbel4https://orcid.org/0000-0002-2875-562XDepartment of Control and Instrumentation Engineering, King Fahd University of Petroleum and Minerals, Dhahran, Saudi ArabiaDepartment of Control and Instrumentation Engineering, King Fahd University of Petroleum and Minerals, Dhahran, Saudi ArabiaDepartment of Control and Instrumentation Engineering, King Fahd University of Petroleum and Minerals, Dhahran, Saudi ArabiaInterdisciplinary Research Centre for Smart Mobility and Logistics, King Fahd University of Petroleum and Minerals, Dhahran, Saudi ArabiaElectrical Engineering Department, Control and Energy Management Laboratory (CEMLab), University of Sfax, Sfax, TunisiaFractional order calculus (FOC) uses arbitrary order operations in differentiation and integration. Previously, the absence of methods to solve fractional differential equations limited the application of fractional order calculus. However, with the development of new methods, FOC is now applicable in various fields and has been utilized to enhance control system performance in traditional techniques. FOC is used in this study to develop a new fractional structure for the sliding mode control approach that offers improved performance and more robustness to external disturbances. The fractional order sliding mode control (FOSMC) strategy is designed using a Lyapunov-based sliding condition to ensure system stability. To enhance performance, genetic algorithms are used to adjust the fractional orders and controller parameters. The proposed fractional sliding mode control system is applied on an unmanned aerial vehicle system affected by external disturbances and then it is compared with a conventional integer order sliding mode control (IOSMC) system. Simulation results have proved the efficiency of the proposed fractional order controller where it outperforms the conventional sliding mode controller in terms of better transient dynamics and more robustness to external disturbances.https://ieeexplore.ieee.org/document/10769462/Sliding mode controlfractional sliding mode controlunmanned aerial vehiclegenetic algorithm |
| spellingShingle | Najib Alabsari Abdul-Wahid A. Saif Sami El-Ferik Salih Duffuaa Nabil Derbel Fractional Order Sliding Mode Control With GA Tuning for a UAV Quadrotor IEEE Access Sliding mode control fractional sliding mode control unmanned aerial vehicle genetic algorithm |
| title | Fractional Order Sliding Mode Control With GA Tuning for a UAV Quadrotor |
| title_full | Fractional Order Sliding Mode Control With GA Tuning for a UAV Quadrotor |
| title_fullStr | Fractional Order Sliding Mode Control With GA Tuning for a UAV Quadrotor |
| title_full_unstemmed | Fractional Order Sliding Mode Control With GA Tuning for a UAV Quadrotor |
| title_short | Fractional Order Sliding Mode Control With GA Tuning for a UAV Quadrotor |
| title_sort | fractional order sliding mode control with ga tuning for a uav quadrotor |
| topic | Sliding mode control fractional sliding mode control unmanned aerial vehicle genetic algorithm |
| url | https://ieeexplore.ieee.org/document/10769462/ |
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