In this paper, a team of cooperative Unmanned Aerial Vehicles (UAVs) maintains a desired geometrical formation while tracking a reference trajectory using a new control approach. Decentralized Learning Based Model Predictive Control (DLBMPC) is a new control technique that combines statistical learning along with control engineering while providing guarantees on safety, robustness and convergence. The ability of the proposed DLBMPC controller in solving the problem of formation for a team of cooperative UAVs is solved in simulation. The designed controller respects the general formation constraints known as Reynolds rules of flocking. Our main contribution in this paper lays in the stabilization of a group of cooperative UAVs, in a desired formation, while tracking a reference trajectory using DLBMPC in the presence of model uncertainties.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Cooperative Unmanned Aerial Vehicles formation via decentralized LBMPC


    Beteiligte:


    Erscheinungsdatum :

    01.06.2015


    Format / Umfang :

    1188208 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Cooperative Formation Control Technology for Manned/Unmanned Aerial Vehicles

    Zheng, Yu / Li, Teng / Niu, Peixing et al. | Springer Verlag | 2019


    Cooperative Localization of Unmanned Aerial Vehicles in Time-Invariant Formation

    Zhang, Jingze / Luo, Zijuan / Li, Chunyu et al. | Springer Verlag | 2024


    Decentralized Task Assignment for Networked Unmanned Aerial Vehicles

    Szarafinski, Hava / Kiriakidis, Kiriakos | IEEE | 2025


    Cooperative path planning of unmanned aerial vehicles

    Tsourdos, Antonios / White, Brian / Shanmugavel, Madhavan | TIBKAT | 2011