Third-Order Sliding Mode Control for Trajectory Tracking of Quadcopters Using Particle Swarm Optimization
This study focuses on designing a controller for trajectory tracking of quadcopters using advanced sliding-mode techniques. Specifically, an integral terminal sliding-mode control based on an adaptive barrier function with a super-twisting reaching law is employed to achieve precise trajectory track...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-02-01
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| Series: | Drones |
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| Online Access: | https://www.mdpi.com/2504-446X/9/3/172 |
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| author | Muhammad Rizwan Chughtai Iftikhar Ahmad Abdullah Mughees Muddesar Iqbal Dhafer Almakhles Mahmoud Abdelrahim |
| author_facet | Muhammad Rizwan Chughtai Iftikhar Ahmad Abdullah Mughees Muddesar Iqbal Dhafer Almakhles Mahmoud Abdelrahim |
| author_sort | Muhammad Rizwan Chughtai |
| collection | DOAJ |
| description | This study focuses on designing a controller for trajectory tracking of quadcopters using advanced sliding-mode techniques. Specifically, an integral terminal sliding-mode control based on an adaptive barrier function with a super-twisting reaching law is employed to achieve precise trajectory tracking. The performance of the controller is enhanced by applying Particle Swarm Optimization to fine-tune the gain values. The nonlinear dynamics of the quadcopter are modeled using the Euler–Lagrange approach, followed by a Lyapunov stability analysis to verify the stability of the controller. The adaptive barrier function is used to prevent control signal saturation, while the third-order sliding-mode controller effectively reduces the chattering. Additionally, a saturation function is introduced to further mitigate the chattering effect. The effectiveness of the proposed approach is demonstrated through numerical simulations, and its performance is further validated through controller-in-the-loop implementation. The results show that the proposed method significantly improves trajectory-tracking accuracy. |
| format | Article |
| id | doaj-art-65d8a39a773845aa806009f28a69b7d7 |
| institution | OA Journals |
| issn | 2504-446X |
| language | English |
| publishDate | 2025-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Drones |
| spelling | doaj-art-65d8a39a773845aa806009f28a69b7d72025-08-20T02:11:22ZengMDPI AGDrones2504-446X2025-02-019317210.3390/drones9030172Third-Order Sliding Mode Control for Trajectory Tracking of Quadcopters Using Particle Swarm OptimizationMuhammad Rizwan Chughtai0Iftikhar Ahmad1Abdullah Mughees2Muddesar Iqbal3Dhafer Almakhles4Mahmoud Abdelrahim5Renewable Energy Laboratory, College of Engineering, Prince Sultan University, Riyadh 11586, Saudi ArabiaSchool of Electrical Engineering and Computer Science, National University of Sciences and Technology, Islamabad 44000, PakistanSchool of Electrical Engineering and Computer Science, National University of Sciences and Technology, Islamabad 44000, PakistanRenewable Energy Laboratory, College of Engineering, Prince Sultan University, Riyadh 11586, Saudi ArabiaRenewable Energy Laboratory, College of Engineering, Prince Sultan University, Riyadh 11586, Saudi ArabiaRenewable Energy Laboratory, College of Engineering, Prince Sultan University, Riyadh 11586, Saudi ArabiaThis study focuses on designing a controller for trajectory tracking of quadcopters using advanced sliding-mode techniques. Specifically, an integral terminal sliding-mode control based on an adaptive barrier function with a super-twisting reaching law is employed to achieve precise trajectory tracking. The performance of the controller is enhanced by applying Particle Swarm Optimization to fine-tune the gain values. The nonlinear dynamics of the quadcopter are modeled using the Euler–Lagrange approach, followed by a Lyapunov stability analysis to verify the stability of the controller. The adaptive barrier function is used to prevent control signal saturation, while the third-order sliding-mode controller effectively reduces the chattering. Additionally, a saturation function is introduced to further mitigate the chattering effect. The effectiveness of the proposed approach is demonstrated through numerical simulations, and its performance is further validated through controller-in-the-loop implementation. The results show that the proposed method significantly improves trajectory-tracking accuracy.https://www.mdpi.com/2504-446X/9/3/172quadcopter UAVcross configurationtrajectory trackingsliding-mode controlparticle swarm optimization |
| spellingShingle | Muhammad Rizwan Chughtai Iftikhar Ahmad Abdullah Mughees Muddesar Iqbal Dhafer Almakhles Mahmoud Abdelrahim Third-Order Sliding Mode Control for Trajectory Tracking of Quadcopters Using Particle Swarm Optimization Drones quadcopter UAV cross configuration trajectory tracking sliding-mode control particle swarm optimization |
| title | Third-Order Sliding Mode Control for Trajectory Tracking of Quadcopters Using Particle Swarm Optimization |
| title_full | Third-Order Sliding Mode Control for Trajectory Tracking of Quadcopters Using Particle Swarm Optimization |
| title_fullStr | Third-Order Sliding Mode Control for Trajectory Tracking of Quadcopters Using Particle Swarm Optimization |
| title_full_unstemmed | Third-Order Sliding Mode Control for Trajectory Tracking of Quadcopters Using Particle Swarm Optimization |
| title_short | Third-Order Sliding Mode Control for Trajectory Tracking of Quadcopters Using Particle Swarm Optimization |
| title_sort | third order sliding mode control for trajectory tracking of quadcopters using particle swarm optimization |
| topic | quadcopter UAV cross configuration trajectory tracking sliding-mode control particle swarm optimization |
| url | https://www.mdpi.com/2504-446X/9/3/172 |
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