Dynamic Soaring in Uncertain Wind Conditions: Polynomial Chaos Expansion Approach

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F24%3APU149411" target="_blank" >RIV/00216305:26230/24:PU149411 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1007/978-3-031-53969-5_9" target="_blank" >http://dx.doi.org/10.1007/978-3-031-53969-5_9</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-031-53969-5_9" target="_blank" >10.1007/978-3-031-53969-5_9</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Dynamic Soaring in Uncertain Wind Conditions: Polynomial Chaos Expansion Approach

Popis výsledku v původním jazyce

Dynamic soaring refers to a flight technique used primarily by large seabirds to extract energy from the wind shear layers formed above ocean surface. A small Unmanned Aerial Vehicle (UAV) capable of efficient dynamic soaring maneuvers can enable long endurance missions in context of patrol or increased flight range. To realize autonomous energy-saving patterns by a UAV, a real-time trajectory generation for a dynamic soaring maneuver accounting for varying external conditions has to be performed. The design of the flight trajectory is formulated as an Optimal Control Problem (OCP) and solved within direct collocation based optimization. A surrogate model of the optimal traveling cycle capturing wind profile uncertainties is constructed using Polynomial Chaos Expansion (PCE). The unknown wind profile parameters are estimated from observed trajectory by means of a Genetic Algorithm (GA). The PCE surrogate model is subsequently utilized to update the optimal trajectory using the estimated wind profile parameters.

Název v anglickém jazyce

Dynamic Soaring in Uncertain Wind Conditions: Polynomial Chaos Expansion Approach

Popis výsledku anglicky

Dynamic soaring refers to a flight technique used primarily by large seabirds to extract energy from the wind shear layers formed above ocean surface. A small Unmanned Aerial Vehicle (UAV) capable of efficient dynamic soaring maneuvers can enable long endurance missions in context of patrol or increased flight range. To realize autonomous energy-saving patterns by a UAV, a real-time trajectory generation for a dynamic soaring maneuver accounting for varying external conditions has to be performed. The design of the flight trajectory is formulated as an Optimal Control Problem (OCP) and solved within direct collocation based optimization. A surrogate model of the optimal traveling cycle capturing wind profile uncertainties is constructed using Polynomial Chaos Expansion (PCE). The unknown wind profile parameters are estimated from observed trajectory by means of a Genetic Algorithm (GA). The PCE surrogate model is subsequently utilized to update the optimal trajectory using the estimated wind profile parameters.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2024

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Machine Learning, Optimization, and Data Science

ISBN

978-3-031-53968-8

ISSN

0302-9743

e-ISSN

—

Počet stran výsledku

11

Strana od-do

104-115

Název nakladatele

Springer Nature Switzerland AG

Místo vydání

Grasmere

Místo konání akce

Grasmere

Datum konání akce

22. 9. 2023

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

—