Detail publikace

LQR Based Digital Autopilot For Light Sport Aircraft

VLK, J. CHUDÝ, P. PRUSTOMĚRSKÝ, M.

Originální název

LQR Based Digital Autopilot For Light Sport Aircraft

Typ

článek ve sborníku ve WoS nebo Scopus

Jazyk

angličtina

Originální abstrakt

This paper addresses research on modern methods in automatic Flight Control System design and evaluation, as seen from the perspective of state-of-the-art and future utilization on Unmanned Aerial Systems. The paper introduces a Flight Control System design process with a special emphasis on the Model-Based Design approach. An integral part of this process is the composition of the aircrafts mathematical model employed in the flight control laws synthesis and the development of a simulation framework for the evaluation of the automatic Flight Control System's stability and performance.The core of this work is aimed at flight control laws synthesis built around the optimal control theory. The researched flight control laws originating from the proposed design process were integrated into an experimental digital Flight Control System.

Klíčová slova

aircraft, autopilot, flight control system, LQR

Autoři

VLK, J.; CHUDÝ, P.; PRUSTOMĚRSKÝ, M.

Vydáno

28. 11. 2022

Nakladatel

International Council of the Aeronautical Sciences

Místo

Stockholm

ISBN

978-1-7138-7116-3

Kniha

33rd Congress of the International Council of the Aeronautical Sciences, ICAS 2022

ISSN

2958-4647

Periodikum

ICAS Proceedings

Ročník

7

Číslo

11

Stát

Spolková republika Německo

Strany od

5321

Strany do

5335

Strany počet

15

URL

BibTex

@inproceedings{BUT182525,
  author="Jan {Vlk} and Peter {Chudý} and Milan {Prustoměrský}",
  title="LQR Based Digital Autopilot For Light Sport Aircraft",
  booktitle="33rd Congress of the International Council of the Aeronautical Sciences, ICAS 2022",
  year="2022",
  journal="ICAS Proceedings",
  volume="7",
  number="11",
  pages="5321--5335",
  publisher="International Council of the Aeronautical Sciences",
  address="Stockholm",
  isbn="978-1-7138-7116-3",
  issn="2958-4647",
  url="https://www.icas.org/ICAS_ARCHIVE/ICAS2022/data/papers/ICAS2022_0719_paper.pdf"
}