Review of Aircraft Aerodynamic Force Parameters Identification based on the Intelligent Algorithm

DOI

10.2991/ccis-13.2013.23How to use a DOI?

Keywords

Aerodynamic Force Parameter Identification; Genetic Algorithm; Particle Swarm Optimization; Artificial Bee Colony Algorithm t (key words).

Abstract

Aerodynamic force parameter identification is the main measure of aerodynamic numerical simulation and wind tunnel test results verification. The wide use of intelligent control in the control field provides a new way to resolve the problem for system identification.Due to the global search optimization ability of intelligent algorithm, it can effectively improve precision and efficiency of aircraft aerodynamic force parameter identification. This paper gives a brief review of system identification method based on intelligent algorithm and its application in aircraft aerodynamic force parameters identification, including genetic algorithm, particle swarm optimization and artificial colony algorithm, etc. In this paper, the research work will provide useful technology reference for the aircraft aerodynamic force parameter identification.

Copyright

© 2013, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Wang Yufei
AU  - Xu Jiacun
AU  - Ge Shen
AU  - Lu Chen
PY  - 2013/11
DA  - 2013/11
TI  - Review of Aircraft Aerodynamic Force Parameters Identification based on the Intelligent Algorithm
BT  - Proceedings of the The 1st International Workshop on Cloud Computing and Information Security
PB  - Atlantis Press
SP  - 94
EP  - 98
SN  - 1951-6851
UR  - https://doi.org/10.2991/ccis-13.2013.23
DO  - 10.2991/ccis-13.2013.23
ID  - Yufei2013/11
ER  -