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Cooperative Circumnavigation with Robust Vector Field Guidance for Multiple UAVs in Unknown Wind Environments

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Abstract

Accounting for wind perturbations while controlling a formation of unmanned aerial vehicles (UAVs) is of a particular interest for researchers: it helps confirm the operability of algorithms in realistic non-laboratory conditions and increases the efficiency of these algorithms. This approach, however, becomes a problem for a decentralized formation due to its interconnected structure. This research work focuses on the problem of accounting for wind perturbations for a fixed-wing UAV formation controlled using the vector field path following method in cooperative or collective circumnavigation. We only study the control based on the local data about nearby UAVs as we consider the consensus-based control. The suggested solution is an adaptive control algorithm studied with Lyapunov functions. At the same time, we conduct computer simulation using complete non-linear UAV models, as well as the comparison with an algorithm that does not account for wind perturbations. As a result, we theoretically demonstrate uniform ultimate boundedness (UUB) of the trajectories of the system in question. Simulation shows that, although the algorithm that does not account for wind perturbations can control a formation with reduced accuracy, the suggested algorithm can improve its efficiency. Therefore, the solution considered in this article helps develop the applicability of consensus-based UAV formation control methods under more realistic conditions and wind impacts.

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Acknowledgements

This work was supported by the Ministry of Science and Higher Education of the Russian Federation (Agreement No. 075-15-2021-1016).

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The Ministry of Science and Higher Education of the Russian Federation (Agreement No. 075–15-2021–1016).

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Tagir Muslimov did all the research and wrote this manuscript.

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Correspondence to Tagir Muslimov.

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Muslimov, T. Cooperative Circumnavigation with Robust Vector Field Guidance for Multiple UAVs in Unknown Wind Environments. J Intell Robot Syst 109, 84 (2023). https://doi.org/10.1007/s10846-023-02000-3

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