This paper proposes a linear parameter varying (LPV) model reference-based control for fixed-wing unmanned aerial vehicles (UAVs), which achieves agile and high performance tracking objectives in extended flight envelopes, e.g. when near stall or deep stall flight conditions are considered. Each of the considered control loops (yaw, pitch and airspeed) delivers an error model that can be reshaped into a quasi-LPV form through an appropriate choice of the scheduling variables. The quasi-LPV error models are suitable for designing error feedback controllers using linear matrix inequalities (LMIs), which are derived within the quadratic Lyapunov framework. Simulation results are used to show the effectiveness of the proposed approach. ; acceptedVersion ; © 2017. This is the authors’ accepted and refereed manuscript to the article. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/


    Zugriff

    Download


    Exportieren, teilen und zitieren



    Titel :

    LPV model reference control for fixed-wing UAVs


    Beteiligte:

    Erscheinungsdatum :

    2017-01-01


    Anmerkungen:

    cristin:1525303
    50 ; IFAC-PapersOnLine ; 1



    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch


    Klassifikation :

    DDC:    629




    FIXED-WING UAVS CONTROL WITH MODEL UNCERTAINTIES

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


    Geometric Reduced-Attitude Control of Fixed-Wing UAVs

    Coates, Erlend M. / Fossen, Thor I. | BASE | 2021

    Freier Zugriff

    Optimizing Endurance in Fixed Wing UAVs

    Sasane, Atharva / Borkar, Srujan / Majety, Prithvi et al. | Springer Verlag | 2024


    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


    Deep Reinforcement Learning Attitude Control of Fixed-Wing UAVs

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