Aircraft Unsteady Aerodynamic Hybrid Modeling Based on State-Space Representation and Neural Network

Ouyang Guang, Lin Jun, Zhang Ping

2016

Abstract

This paper proposes a hybrid model which combines state-space representation and back-propagation neural network to describe the aircraft unsteady aerodynamic characteristics. Firstly, the state-space model is analysed and evaluated using wind-tunnel experimental data. Subsequently, back-propagation neural network is introduced and combined with state-space representation to form a hybrid model. In this hybrid model, the separation point model in state-space representation is reserved to describe the time delay of the unsteady aerodynamic responses, while the conventional polynomial model is replaced by back-propagation neural network to improve accuracy and universality. Finally, lift coefficient and pitch moment coefficient data from the wind-tunnel experiments are used to estimate the hybrid model. With high similarity to the wind-tunnel data, the hybrid model presented in this paper is proved to be accurate and effective for aircraft unsteady aerodynamic modeling.

Paper Citation

in Harvard Style

Guang O., Jun L. and Ping Z. (2016). Aircraft Unsteady Aerodynamic Hybrid Modeling Based on State-Space Representation and Neural Network . In Proceedings of the 5th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, ISBN 978-989-758-173-1, pages 232-239. DOI: 10.5220/0005691702320239

in Bibtex Style

@conference{icpram16,
author={Ouyang Guang and Lin Jun and Zhang Ping},
title={Aircraft Unsteady Aerodynamic Hybrid Modeling Based on State-Space Representation and Neural Network},
booktitle={Proceedings of the 5th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,},
year={2016},
pages={232-239},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005691702320239},
isbn={978-989-758-173-1},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 5th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,
TI - Aircraft Unsteady Aerodynamic Hybrid Modeling Based on State-Space Representation and Neural Network
SN - 978-989-758-173-1
AU - Guang O.
AU - Jun L.
AU - Ping Z.
PY - 2016
SP - 232
EP - 239
DO - 10.5220/0005691702320239