Publication Details
Dynamic Soaring in Uncertain Wind Conditions: Polynomial Chaos Expansion Approach
Polynomial Chaos Expansion, Surrogate Modeling, Dynamic Soaring, Optimal
Control
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.
@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"
}