Data-driven identification of vehicle dynamics using Koopman operator

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F19%3A00332651" target="_blank" >RIV/68407700:21230/19:00332651 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1109/PC.2019.8815104" target="_blank" >http://dx.doi.org/10.1109/PC.2019.8815104</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/PC.2019.8815104" target="_blank" >10.1109/PC.2019.8815104</a>

Result language
angličtina
Original language name
Data-driven identification of vehicle dynamics using Koopman operator
Original language description
This paper presents the results of identification of vehicle dynamics using the Koopman operator. The basic idea is to transform the state space of a nonlinear system (a car in our case) to a higher-dimensional space, using so-called basis functions, where the system dynamics is linear. The selection of basis functions is crucial and there is no general approach on how to select them, this paper gives some discussion on this topic. Two distinct approaches for selecting the basis functions are presented. The first approach, based on Extended Dynamic Mode Decomposition, relies heavily on expert basis selection and is completely data-driven. The second approach utilizes the knowledge of the nonlinear dynamics, which is used to construct eigenfunctions of the Koopman operator which are known by definition to evolve linearly along the nonlinear system trajectory. The eigenfunctions are then used as basis functions for prediction. Each approach is presented with a numerical example and discussion on the feasibility of the approach for a nonlinear vehicle system.
Czech name
—
Czech description
—

Project
<a href="/en/project/GA19-16772S" target="_blank" >GA19-16772S: Aerodynamic bodies with actively controlled morphing</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Proceedings of the 22nd International Conference on Process Control
ISBN
978-1-7281-3758-2
ISSN
—
e-ISSN
—
Number of pages
6
Pages from-to
167-172
Publisher name
IEEE
Place of publication
Piscataway, NJ
Event location
Štrbské Pleso
Event date
Jun 11, 2019
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000539039300030

Similar results(10)