This paper introduces a new formulation of model predictive control for robust trajectory guidance of unmanned aerial vehicles. It generalizes the ubiquitous concept of waypoints to waysets, in order to provide robustness to bounded state disturbances in the presence of obstacles. Using a variable horizon formulation of model predictive control, it shows how wayset guidance combined with constraint tightening can guarantee robust recursive feasibility and finite-time completion of a control maneuver. Simulations on a point mass fixed-wing unmanned aerial vehicle model moving through a field of obstacles with wind disturbances demonstrate significant computational benefits from using waysets when compared to existing mixed-integer optimization methods that employ long prediction horizons. Using the controller’s robustness to mitigate linearization error, an additional example implements the strategy on a simulated quadrotor, demonstrating how waysets can be used to control more complex nonlinear systems.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Robust Model Predictive Control of Unmanned Aerial Vehicles Using Waysets


    Contributors:

    Published in:

    Publication date :

    2015-10-01




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English





    Distributed model predictive control for unmanned aerial vehicles

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


    Unmanned aerial vehicles formation using learning based model predictive control

    Hafez, Ahmed T. / Givigi, Sidney N. / Yousefi, Shahram | British Library Online Contents | 2018


    Model Predictive Path Integral Control for Agile Unmanned Aerial Vehicles

    Minarik, Michal / Penicka, Robert / Vonasek, Vojtech et al. | ArXiv | 2024

    Free access

    Flight Time Improvement Using Adaptive Model Predictive Control for Unmanned Aerial Vehicles

    Ngo, Huy-Hoang / Canh, Thanh Nguyen / HoangVan, Xiem | ArXiv | 2024

    Free access