This paper introduces a Nonlinear Model Predictive Control (NMPC) approach for the path-following control of fixed-wing unmanned aerial vehicles (UAVs). Unlike other NMPC approaches that rely on kinematic guidance models or control-augmented dynamics, the proposed NMPC is implemented directly at the actuator level, eliminating the need for a lower-level flight-control loop. The performance of the proposed NMPC is evaluated through numerical simulations. The results demonstrate the controller’s robustness in accurately tracking high-curvature parametric paths, particularly for short prediction horizons. Furthermore, the feasibility of real-time implementation on embedded computing platforms onboard a fixed-wing UAV is discussed.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Fixed-Wing UAV Path-Following Control via NMPC on the Lowest Level


    Beteiligte:


    Erscheinungsdatum :

    16.08.2023


    Format / Umfang :

    1833102 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Direct NMPC for Post-Stall Motion Planning with Fixed-Wing UAVs

    Basescu, Max / Moore, Joseph | ArXiv | 2020

    Freier Zugriff

    Learning-based NMPC Framework for Car Racing Cinematography Using Fixed-Wing UAV

    Soni, Dev / Manoharan, Amith / Tyagi, Prakrit et al. | IEEE | 2022




    Time-Optimal Path Following for Fixed-Wing Aircraft

    Zhao, Yiming / Tsiotras, Panagiotis | AIAA | 2013