We propose the combination of a Nonlinear Model Predictive Controller (NMPC) with a Geometric Controller (GC) for the attitude and speed control problem of fixed-wing unmanned aerial vehicles (UAVs). The NMPC sends reference vectors for attitude, angular rates and angular acceleration to the low-level GC that can be run at a significantly higher bandwidth. This way we generate optimal references for the GC, increase its region of attraction while also addressing performance and constraint satisfaction. The efficacy of the proposed approach is illustrated in numerical simulation examples.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Nonlinear Model Predictive Control combined with Geometric Attitude and Speed Control for Fixed-Wing UAVs


    Contributors:


    Publication date :

    2021-06-15


    Size :

    972418 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Deep Reinforcement Learning Attitude Control of Fixed-Wing UAVs

    Zhen, Yan / Hao, Mingrui / Sun, Wendi | IEEE | 2020




    FIXED-WING UAVS CONTROL WITH MODEL UNCERTAINTIES

    Kartal, M. / Ignatyev, D. / Zolotas, A. | British Library Conference Proceedings | 2022


    ICAS2016_0326: MODEL PREDICTIVE CONTROL FOR A SWARM OF FIXED WING UAVS

    Ariola, M. / Mattei, M. / D Amato, E. et al. | British Library Conference Proceedings | 2016