Optimization of Thrust-Augmented Dynamic Soaring

Gottfried Sachs () and Benedikt Grüter ()
Additional contact information
Gottfried Sachs: Technische Universitaet Muenchen
Benedikt Grüter: Technische Universitaet Muenchen

Journal of Optimization Theory and Applications, 2022, vol. 192, issue 3, No 8, 960-978

Abstract: Abstract Dynamic soaring is a non-powered flight mode that enables to fly at no cost by gaining energy from a horizontal shear wind. This is not possible if the shear wind strength is too low. Engine thrust is introduced as a means to augment dynamic soaring in shear winds with insufficient strength. Appropriate models of the vehicle dynamics and the shear wind are developed, and an optimization method is used to construct results on optimal thrust-augmented dynamic soaring. The minimum energy required from the propulsion system is determined for the entire region of insufficient shear wind strength down to zero wind. Solutions of the characteristics of the motion including states and controls are presented. Furthermore, it is shown what a control simplification in terms of an optimal constant power setting as an ease of control yields for the energy required from the propulsion system.

Keywords: Power-augmented dynamic soaring; Dynamic soaring at low wind; Optimal power control (search for similar items in EconPapers)
Date: 2022
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s10957-021-01999-5 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:joptap:v:192:y:2022:i:3:d:10.1007_s10957-021-01999-5

Ordering information: This journal article can be ordered from
http://www.springer. ... cs/journal/10957/PS2

DOI: 10.1007/s10957-021-01999-5

Access Statistics for this article

Journal of Optimization Theory and Applications is currently edited by Franco Giannessi and David G. Hull

More articles in Journal of Optimization Theory and Applications from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().