2020
DOI: 10.1109/tcst.2019.2912345
|View full text |Cite
|
Sign up to set email alerts
|

Iterative Learning-Based Path Optimization for Repetitive Path Planning, With Application to 3-D Crosswind Flight of Airborne Wind Energy Systems

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1
1

Citation Types

0
25
0

Year Published

2020
2020
2024
2024

Publication Types

Select...
7
1

Relationship

1
7

Authors

Journals

citations
Cited by 40 publications
(25 citation statements)
references
References 22 publications
0
25
0
Order By: Relevance
“…However, most of the optimization methods require the gradient of the index function [32]- [34] to iteratively update η j . This part introduces an RLS-based estimator that has the same structure as the one designed in [35] to estimate the gradient of H (η j ) and the Adam optimization method is applied to iteratively find the optimal solution of Eq. (20).…”
Section: ) Estimation Of Characteristic Parameter Of Upper Limbmentioning
confidence: 99%
“…However, most of the optimization methods require the gradient of the index function [32]- [34] to iteratively update η j . This part introduces an RLS-based estimator that has the same structure as the one designed in [35] to estimate the gradient of H (η j ) and the Adam optimization method is applied to iteratively find the optimal solution of Eq. (20).…”
Section: ) Estimation Of Characteristic Parameter Of Upper Limbmentioning
confidence: 99%
“…Because this requires a more detailed aerodynamic and flight dynamic characterization of the lifting body, comprised of airfoils, the resulting model is termed the unifoil model. The model is detailed in Cobb, Barton, Fathy, and Vermillion (2019b) and is summarized here.…”
Section: The Unifoil Modelmentioning
confidence: 99%
“…The expressions for 𝐹 long and 𝑀 rot can be quite complicated, as they depend on detailed aerodynamic relationships. Readers are referred to Cobb et al (2019b) for further details in this regard.…”
Section: The Unifoil Modelmentioning
confidence: 99%
“…In classical ILC, the controller uses tracking error ata from previous task iterations to better track the provided trajectory during the current iteration. Recent work has also explored reference-free ILC for applications whose goals are better defined through a performance metric, such as autonomous racing or harvesting wind energy [4]- [6].…”
Section: Note To Practitionersmentioning
confidence: 99%