Aerodynamic coefficients modeling using Levenberg–Marquardt algorithm and network
Aircraft Engineering and Aerospace Technology
ISSN: 0002-2667
Article publication date: 23 October 2021
Issue publication date: 10 February 2022
Abstract
Purpose
The purpose of this paper is to propose a new aerodynamic parameter estimation methodology based on neural network and output error method, while the output error method is improved based on particle swarm algorithm.
Design/methodology/approach
Firstly, the algorithm approximates the dynamic characteristics of aircraft based on feedforward neural network. Neural network is trained by extreme learning machine, and the trained network can predict the aircraft response at (k + 1)th instant given the measured flight data at kth instant. Secondly, particle swarm optimization is used to enhance the convergence of Levenberg–Marquardt (LM) algorithm, and the improved LM method is used to substitute for the Gauss Newton algorithm in output error method. Finally, the trained neural network is combined with the improved output error method to estimate aerodynamic derivatives.
Findings
Neither depending on the initial guess of the parameters to be estimated nor requiring numerical integration of the aircraft motion equation, the proposed algorithm can be used for unstable aircraft and is successfully applied to extract aerodynamic derivatives from both simulated and real flight data.
Research limitations/implications
The proposed method requires iterative calculation and can only identify parameters offline.
Practical implications
The proposed method is successfully applied to estimate aircraft aerodynamic parameters and can also be used as a new algorithm for other optimization problems.
Originality/value
In this study, the output error method is improved to reduce the dependence on the initial value of parameters and expand its application scope. It is applied in aircraft aerodynamic parameter identification together with neural network.
Keywords
Acknowledgements
The authors express their sincere appreciation for the support of the National Natural Science Foundation of China under Grant No. 51808447 and the Aeronautical Science Foundation of China under Grant Nos 20180753005 and 201958053003.
Further work: The research limitation is that the proposed method requires iterative calculation and can only identify parameters offline, and analysis is carried out at 1 trim point. Next, the authors’ team will study the aerodynamic coefficient modeling in the full envelope range and in real time and attempt to build models with long-duration response prediction capabilities based on higher quality and richer flight test data.
Citation
Wang, Z., Li, A., Wang, L., Zhou, X. and Wu, B. (2022), "Aerodynamic coefficients modeling using Levenberg–Marquardt algorithm and network", Aircraft Engineering and Aerospace Technology, Vol. 94 No. 3, pp. 336-350. https://doi.org/10.1108/AEAT-03-2021-0073
Publisher
:Emerald Publishing Limited
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