loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Authors: Daniel Fenyes 1 ; Tamas Hegedus 1 ; Vu Van Tan 2 and Peter Gaspar 1 ; 3

Affiliations: 1 Institute for Computer Science and Control (SZTAKI), Eötvös Loránd Research Network (ELKH), Kende u. 13-17, H-1111 Budapest, Hungary ; 2 Department of Automotive Mechanical Engineering, Faculty of Mechanical Engineering, University of Transport and Communications, 3 Cau Giay Street, 100000 Hanoi, Vietnam ; 3 Department of Control for Transportation and Vehicle Systems, Budapest University of Technology and Economics, Stoczek u. 2, H-1111 Budapest, Hungary

Keyword(s): Observer, Model-Free Control, Ultra-Local Model, Lateral Velocity, Autonomous Vehicles.

Abstract: The paper presents a novel observer design algorithm for autonomous vehicles. The technique is based on the combination of a classical linear observer and the ultra-local model. The linear observer is easy to design and it requires only a linear model of the considered system. However, it performs poorly when the linear system cannot cover the system’s dynamics due to nonlinearities or unmodelled dynamics. The ultra-local model aims to compensate for the nonlinear effects and improve the overall performances of the observer. The proposed method is applied to a vehicle-oriented estimation problem: lateral velocity. The operation and the effectiveness of the presented algorithm is demonstrated through several test scenarios in CarSim and also using real-test measurements.

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 3.21.248.119

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Fenyes, D.; Hegedus, T.; Van Tan, V. and Gaspar, P. (2023). An Observer Design Method Using Ultra-Local Model for Autonomous Vehicles. In Proceedings of the 20th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO; ISBN 978-989-758-670-5; ISSN 2184-2809, SciTePress, pages 41-49. DOI: 10.5220/0012184300003543

@conference{icinco23,
author={Daniel Fenyes. and Tamas Hegedus. and Vu {Van Tan}. and Peter Gaspar.},
title={An Observer Design Method Using Ultra-Local Model for Autonomous Vehicles},
booktitle={Proceedings of the 20th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO},
year={2023},
pages={41-49},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012184300003543},
isbn={978-989-758-670-5},
issn={2184-2809},
}

TY - CONF

JO - Proceedings of the 20th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO
TI - An Observer Design Method Using Ultra-Local Model for Autonomous Vehicles
SN - 978-989-758-670-5
IS - 2184-2809
AU - Fenyes, D.
AU - Hegedus, T.
AU - Van Tan, V.
AU - Gaspar, P.
PY - 2023
SP - 41
EP - 49
DO - 10.5220/0012184300003543
PB - SciTePress

- Science and Technology Publications, Lda.
RESOURCES

Proceedings

Papers

Authors

Ontology

CONTACTS

Science and Technology Publications, Lda
Avenida de S. Francisco Xavier, Lote 7 Cv. C,
2900-616 Setúbal, Portugal.

Phone: +351 265 520 185 (National fixed network call)
Fax: +351 265 520 186
Email: info@scitepress.org

EXTERNAL LINKS

PRIMORIS

INSTICC

SCITEVENTS

CROSSREF

PROCEEDINGS SUBMITTED FOR INDEXATION BY:

dblp

Ei Compendex

SCOPUS

Semantic Scholar

Google Scholar

Microsoft Academic