Highly dynamic systems such as Micro Multirotor Aerial Vehicles (Micro-MAVs) require control approaches that enable safe operation where extreme limitations in embedded systems, such as energy, processing capability and memory, are present. Nonlinear model predictive control (NMPC) approaches can respect operational constraints in a safe manner. However, they are typically challenging to implement using embedded computers on-board of Micro-MAVs. Implementations of classic NMPC approaches rely on high-performance computers. In this work, we propose a fast nonlinear model predictive control approach that ensures the stabilization and control of Micro Multirotor Aerial Vehicles (Micro-MAVs). This aerial robotic system uses a low processing power board that relies solely on on-board sensors to localize itself, which makes it suitable for experiments in GPS-denied environments. The proposed approach has been verified in numerical simulations using processing capabilities that are available on Micro-MAVs.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Fast Nonlinear Model Predictive Control for Very-Small Aerial Vehicles


    Beteiligte:


    Erscheinungsdatum :

    01.09.2020


    Format / Umfang :

    1147728 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch





    Distributed model predictive control for unmanned aerial vehicles

    Mansouri, Sina Sharif / Nikolakopoulos, George / Gustafsson, Thomas | IEEE | 2015


    Robust Collision Avoidance for Multiple Micro Aerial Vehicles Using Nonlinear Model Predictive Control

    Kamel, Mina / Alonso-Mora, Javier / Siegwart, Roland et al. | BASE | 2017

    Freier Zugriff