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Rethinking Sampled-Data Control for Unmanned Aircraft Systems

Unmanned aircraft systems are expected to provide both increasingly varied functionalities and outstanding application performances, utilizing the available resources. In this paper, we explore the recent advances and challenges at the intersection of real-time computing and control and show how ret...

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Detalles Bibliográficos
Autores principales: Zhang, Xinkai, Bradley, Justin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8880505/
https://www.ncbi.nlm.nih.gov/pubmed/35214425
http://dx.doi.org/10.3390/s22041525
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author Zhang, Xinkai
Bradley, Justin
author_facet Zhang, Xinkai
Bradley, Justin
author_sort Zhang, Xinkai
collection PubMed
description Unmanned aircraft systems are expected to provide both increasingly varied functionalities and outstanding application performances, utilizing the available resources. In this paper, we explore the recent advances and challenges at the intersection of real-time computing and control and show how rethinking sampling strategies can improve performance and resource utilization. We showcase a novel design framework, cyber-physical co-regulation, which can efficiently link together computational and physical characteristics of the system, increasing robust performance and avoiding pitfalls of event-triggered sampling strategies. A comparison experiment of different sampling and control strategies was conducted and analyzed. We demonstrate that co-regulation has resource savings similar to event-triggered sampling, but maintains the robustness of traditional fixed-periodic sampling forming a compelling alternative to traditional vehicle control design.
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spelling pubmed-88805052022-02-26 Rethinking Sampled-Data Control for Unmanned Aircraft Systems Zhang, Xinkai Bradley, Justin Sensors (Basel) Article Unmanned aircraft systems are expected to provide both increasingly varied functionalities and outstanding application performances, utilizing the available resources. In this paper, we explore the recent advances and challenges at the intersection of real-time computing and control and show how rethinking sampling strategies can improve performance and resource utilization. We showcase a novel design framework, cyber-physical co-regulation, which can efficiently link together computational and physical characteristics of the system, increasing robust performance and avoiding pitfalls of event-triggered sampling strategies. A comparison experiment of different sampling and control strategies was conducted and analyzed. We demonstrate that co-regulation has resource savings similar to event-triggered sampling, but maintains the robustness of traditional fixed-periodic sampling forming a compelling alternative to traditional vehicle control design. MDPI 2022-02-16 /pmc/articles/PMC8880505/ /pubmed/35214425 http://dx.doi.org/10.3390/s22041525 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Zhang, Xinkai
Bradley, Justin
Rethinking Sampled-Data Control for Unmanned Aircraft Systems
title Rethinking Sampled-Data Control for Unmanned Aircraft Systems
title_full Rethinking Sampled-Data Control for Unmanned Aircraft Systems
title_fullStr Rethinking Sampled-Data Control for Unmanned Aircraft Systems
title_full_unstemmed Rethinking Sampled-Data Control for Unmanned Aircraft Systems
title_short Rethinking Sampled-Data Control for Unmanned Aircraft Systems
title_sort rethinking sampled-data control for unmanned aircraft systems
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8880505/
https://www.ncbi.nlm.nih.gov/pubmed/35214425
http://dx.doi.org/10.3390/s22041525
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