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.
In-Flight Nonlinear System Identification for UAS Adaptive Control
Sustainable aviat.
International Symposium on Unmanned Systems and The Defense Industry ; 2021 ; Washington, DC, DC, USA October 26, 2021 - October 28, 2021
2023-06-28
8 pages
Aufsatz/Kapitel (Buch)
Elektronische Ressource
Englisch
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