Path Scheduling and Target Trajectory Optimization in UAVs Based on Dragonfly and Firefly Algorithm
It is hoped that there will never be a war in the world, but one of the defensive requirements of any country during the war is the using Unmanned Aerial Vehicle used for destruction and defense. Today, UAVs movement from origin to destination is an important problem due to the abundant application...
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Bilijipub publisher
2022-10-01
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| Series: | Advances in Engineering and Intelligence Systems |
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| Online Access: | https://aeis.bilijipub.com/article_158401_a2d6b8e54d78ea165a28b4b1dd345471.pdf |
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| author | Methaq Hadi Lafta |
| author_facet | Methaq Hadi Lafta |
| author_sort | Methaq Hadi Lafta |
| collection | DOAJ |
| description | It is hoped that there will never be a war in the world, but one of the defensive requirements of any country during the war is the using Unmanned Aerial Vehicle used for destruction and defense. Today, UAVs movement from origin to destination is an important problem due to the abundant application of UAVs in wars and experimental research. This is important because the range of some UAVs in fly time is low, and others are very high due to their fuel. Parametric indeterminacy is several factors in UAVs movement prediction and trajectory, such as speed, movement angle, accuracy, movement time, and situation and direct control. So this research is trying to provide a method based on LQG controller with and then set motion and specify path scheduling without deviations based on swarm intelligence algorithms in combinational mode: Dragonfly-Firefly algorithm. The simulation results showed that the UAV power consumption is comparable to 56.2045 mW, which signifies a prosperous pass. Mean Square Error, Peak Signal to Noise Ratio, Signal-to-Noise Ratio, and Accuracy Criteria will all be used in this study. Based on the results of the evaluation criteria, it is feasible to ensure that the recommended technique will be used for UAV route scheduling and target trajectory optimization when the project is finished. |
| format | Article |
| id | doaj-art-3b850f1d7fa649c5902de4499f61321e |
| institution | Kabale University |
| issn | 2821-0263 |
| language | English |
| publishDate | 2022-10-01 |
| publisher | Bilijipub publisher |
| record_format | Article |
| series | Advances in Engineering and Intelligence Systems |
| spelling | doaj-art-3b850f1d7fa649c5902de4499f61321e2025-02-12T08:46:31ZengBilijipub publisherAdvances in Engineering and Intelligence Systems2821-02632022-10-0100103668010.22034/aeis.2022.356205.1037158401Path Scheduling and Target Trajectory Optimization in UAVs Based on Dragonfly and Firefly AlgorithmMethaq Hadi Lafta0Iraqi Ministry of Education, IraqIt is hoped that there will never be a war in the world, but one of the defensive requirements of any country during the war is the using Unmanned Aerial Vehicle used for destruction and defense. Today, UAVs movement from origin to destination is an important problem due to the abundant application of UAVs in wars and experimental research. This is important because the range of some UAVs in fly time is low, and others are very high due to their fuel. Parametric indeterminacy is several factors in UAVs movement prediction and trajectory, such as speed, movement angle, accuracy, movement time, and situation and direct control. So this research is trying to provide a method based on LQG controller with and then set motion and specify path scheduling without deviations based on swarm intelligence algorithms in combinational mode: Dragonfly-Firefly algorithm. The simulation results showed that the UAV power consumption is comparable to 56.2045 mW, which signifies a prosperous pass. Mean Square Error, Peak Signal to Noise Ratio, Signal-to-Noise Ratio, and Accuracy Criteria will all be used in this study. Based on the results of the evaluation criteria, it is feasible to ensure that the recommended technique will be used for UAV route scheduling and target trajectory optimization when the project is finished.https://aeis.bilijipub.com/article_158401_a2d6b8e54d78ea165a28b4b1dd345471.pdfunmanned aerial vehiclespath schedulingtarget trajectorylqg controllerdragonfly algorithmfirefly algorithm |
| spellingShingle | Methaq Hadi Lafta Path Scheduling and Target Trajectory Optimization in UAVs Based on Dragonfly and Firefly Algorithm Advances in Engineering and Intelligence Systems unmanned aerial vehicles path scheduling target trajectory lqg controller dragonfly algorithm firefly algorithm |
| title | Path Scheduling and Target Trajectory Optimization in UAVs Based on Dragonfly and Firefly Algorithm |
| title_full | Path Scheduling and Target Trajectory Optimization in UAVs Based on Dragonfly and Firefly Algorithm |
| title_fullStr | Path Scheduling and Target Trajectory Optimization in UAVs Based on Dragonfly and Firefly Algorithm |
| title_full_unstemmed | Path Scheduling and Target Trajectory Optimization in UAVs Based on Dragonfly and Firefly Algorithm |
| title_short | Path Scheduling and Target Trajectory Optimization in UAVs Based on Dragonfly and Firefly Algorithm |
| title_sort | path scheduling and target trajectory optimization in uavs based on dragonfly and firefly algorithm |
| topic | unmanned aerial vehicles path scheduling target trajectory lqg controller dragonfly algorithm firefly algorithm |
| url | https://aeis.bilijipub.com/article_158401_a2d6b8e54d78ea165a28b4b1dd345471.pdf |
| work_keys_str_mv | AT methaqhadilafta pathschedulingandtargettrajectoryoptimizationinuavsbasedondragonflyandfireflyalgorithm |