Fast aircraft prototyping, fault detection, morphing surfaces, and real-time generation of dynamic models are just some of the advantages of a model identification adaptive controller. The research presented in this chapter investigates a proposed control architecture and validates the novel data-driven algorithm SINDy to be used for online system identification of a UAS. The reported simulation results explore the effects and the limits of short training time and sensor noise on the identified model fitness.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    In-Flight Nonlinear System Identification for UAS Adaptive Control


    Weitere Titelangaben:

    Sustainable aviat.


    Beteiligte:
    Karakoc, T. Hikmet (Herausgeber:in) / Yilmaz, Nadir (Herausgeber:in) / Dalkiran, Alper (Herausgeber:in) / Ercan, Ali Haydar (Herausgeber:in) / Bazzocchi, Sean (Autor:in) / Suleman, Afzal (Autor:in)

    Kongress:

    International Symposium on Unmanned Systems and The Defense Industry ; 2021 ; Washington, DC, DC, USA October 26, 2021 - October 28, 2021



    Erscheinungsdatum :

    2023-06-28


    Format / Umfang :

    8 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




    Nonlinear Analysis of Adaptive Flight Control Laws

    Seiler, P. / Balas, G. / Dorobantu, A. et al. | British Library Conference Proceedings | 2010


    Adaptive Control via Flight Segment Identification

    BRADSHAW, T.B. / HUBER, R.R. | AIAA | 1982


    Nonlinear Analysis of Adaptive Flight Control Laws

    Dorobantu, Andrei / Seiler, Peter / Balas, Gary | AIAA | 2010


    Nonlinear adaptive flight control using neural networks

    Calise, A.J. / Rysdyk, R.T. | Tema Archiv | 1998