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.


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    Title :

    In-Flight Nonlinear System Identification for UAS Adaptive Control


    Additional title:

    Sustainable aviat.


    Contributors:

    Conference:

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



    Publication date :

    2023-06-28


    Size :

    8 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




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