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2024 | OriginalPaper | Chapter

10. Non-linear System Identification for UAS Adaptive Control

Authors : Sean Bazzocchi, Afzal Suleman

Published in: Unmanned Aerial Vehicle Design and Technology

Publisher: Springer International Publishing

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Abstract

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 (MIAC). The research presented in this paper introduces a MIAC architecture and validates a novel data-driven algorithm to be used for online system identification of unmanned aerial system (UAS). The simulation results illustrate the effects and the limits of short training time and sensor noise on the identified model.

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Title: Non-linear System Identification for UAS Adaptive Control
Authors: Sean Bazzocchi
Afzal Suleman
Publisher: Springer International Publishing
Book: Unmanned Aerial Vehicle Design and Technology
Print ISBN: 978-3-031-45320-5

Electronic ISBN: 978-3-031-45321-2

Copyright Year: 2024
DOI: https://doi.org/10.1007/978-3-031-45321-2_10