Detail publikace

Dynamic Soaring in Uncertain Wind Conditions: Polynomial Chaos Expansion Approach

NOVÁK, J. CHUDÝ, P.

Originální název

Dynamic Soaring in Uncertain Wind Conditions: Polynomial Chaos Expansion Approach

Typ

článek ve sborníku ve WoS nebo Scopus

Jazyk

angličtina

Originální abstrakt

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.

Klíčová slova

Polynomial Chaos Expansion, Surrogate Modeling,  Dynamic Soaring, Optimal Control

Autoři

NOVÁK, J.; CHUDÝ, P.

Vydáno

16. 2. 2024

Nakladatel

Springer Nature Switzerland AG

Místo

Grasmere

ISBN

978-3-031-53968-8

Kniha

Machine Learning, Optimization, and Data Science

Edice

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

ISSN

0302-9743

Periodikum

Lecture Notes in Computer Science

Číslo

14505

Stát

Spolková republika Německo

Strany od

104

Strany do

115

Strany počet

11

BibTex

@inproceedings{BUT185184,
  author="Jiří {Novák} and Peter {Chudý}",
  title="Dynamic Soaring in Uncertain Wind Conditions: Polynomial Chaos Expansion Approach",
  booktitle="Machine Learning, Optimization, and Data Science",
  year="2024",
  series="Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
  journal="Lecture Notes in Computer Science",
  number="14505",
  pages="104--115",
  publisher="Springer Nature Switzerland AG",
  address="Grasmere",
  doi="10.1007/978-3-031-53969-5\{_}9",
  isbn="978-3-031-53968-8",
  issn="0302-9743"
}