Trajectory Tracking for UAVs: An Interpolating Control Approach
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arXiv
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| Auteurs principaux: | , , |
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| Format: | Preprint |
| Publié: |
2024
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| _version_ | 1866916406533029888 |
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| author | Bouček, Zdeněk Flídr, Miroslav Straka, Ondřej |
| author_facet | Bouček, Zdeněk Flídr, Miroslav Straka, Ondřej |
| contents | Building on our previous work, this paper investigates the effectiveness of interpolating control (IC) for real-time trajectory tracking. Unlike prior studies that focused on trajectory tracking itself or UAV stabilization control in simulation, we evaluate the performance of a modified extended IC (eIC) controller compared to Model Predictive Control (MPC) through both simulated and laboratory experiments with a remotely controlled UAV.
The evaluation focuses on the computational efficiency and control quality of real-time UAV trajectory tracking compared to previous IC applications. The results demonstrate that the eIC controller achieves competitive performance compared to MPC while significantly reducing computational complexity, making it a promising alternative for resource-constrained platforms. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2407_01095 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Trajectory Tracking for UAVs: An Interpolating Control Approach Bouček, Zdeněk Flídr, Miroslav Straka, Ondřej Systems and Control Robotics Building on our previous work, this paper investigates the effectiveness of interpolating control (IC) for real-time trajectory tracking. Unlike prior studies that focused on trajectory tracking itself or UAV stabilization control in simulation, we evaluate the performance of a modified extended IC (eIC) controller compared to Model Predictive Control (MPC) through both simulated and laboratory experiments with a remotely controlled UAV. The evaluation focuses on the computational efficiency and control quality of real-time UAV trajectory tracking compared to previous IC applications. The results demonstrate that the eIC controller achieves competitive performance compared to MPC while significantly reducing computational complexity, making it a promising alternative for resource-constrained platforms. |
| title | Trajectory Tracking for UAVs: An Interpolating Control Approach |
| topic | Systems and Control Robotics |
| url | https://arxiv.org/abs/2407.01095 |