Inverse problem of aircraft structural parameter identification: application of genetic algorithms compared with artificial neural networks

Trivailo, P, Gilbert, T, Glessich, E and Sgarioto, D 2006, 'Inverse problem of aircraft structural parameter identification: application of genetic algorithms compared with artificial neural networks', Journal on Inverse Problems in Science and Engineering, vol. 14, no. 4, pp. 337-350.


Document type: Journal Article
Collection: Journal Articles

Title Inverse problem of aircraft structural parameter identification: application of genetic algorithms compared with artificial neural networks
Author(s) Trivailo, P
Gilbert, T
Glessich, E
Sgarioto, D
Year 2006
Journal name Journal on Inverse Problems in Science and Engineering
Volume number 14
Issue number 4
Start page 337
End page 350
Total pages 14
Publisher Taylor and Francis
Abstract This article is the second part of a two paper series exploring the application of two advanced computing techniques: artificial neural networks (ANNs) and genetic algorithms (GAs), to the problem of structural parameter identification for an idealised model of an aircraft wing. In this article, GAs are used to determine an idealised finite element model that is representative of the wing of the Pilatus PC-9/A trainer aircraft. This is achieved through an optimisation process that attempts to match the static and dynamic response of the model to measured aircraft structural responses. A number of approaches were trialed with improvements made to each successive approach in an attempt to find a suitable unique parameter set. Structural parameters were found for a three-element model which has characteristics very similar to those of the PC-9/A wing. A comparison is also provided between the performance of the neural network and GA approaches.
Subject Aerospace Engineering not elsewhere classified
Keyword(s) Genetic algorithms
parameter estimation
aircraft structures
finite elements
DOI - identifier 10.1080/17415970600573338
ISSN 1741-5977
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