Neural Networks Modelling for Aircraft Flight Guidance Dynamics - Archive ouverte HAL Accéder directement au contenu
Article Dans Une Revue Journal of Aerospace Technology and Management Année : 2012

Neural Networks Modelling for Aircraft Flight Guidance Dynamics

(1) , (2) , (3) , (4)
1
2
3
4

Résumé

The sustained increase of the air transportation sector over the last decades has led to traffic saturated situations, inducing higher costs for airlines and important negative impacts for airport surrounding communities. The efficient management of air traffic supposes that aircraft trajectories are fully mastered and their impacts can be accurately forecasted. Inversion of aircraft flight dynamics, which are essentially nonlinear, appears necessary. Aircraft flight dynamics is shown to be differentially flat, which is a property that has enabled the development of new numerical tools for the management of complex nonlinear dynamic systems. However, since in the case of aircraft flight dynamics this differential flatness property is implicit, a neural network is introduced to deal with its numerical inversion. Results related to the developed neural network training are displayed, while potential uses of the proposed tool are discussed.
Fichier principal
Vignette du fichier
Mora-Camino_JATM2012.pdf (1.04 Mo) Télécharger le fichier
Origine : Fichiers éditeurs autorisés sur une archive ouverte

Dates et versions

hal-01002817 , version 1 (06-06-2014)

Identifiants

Citer

Wen-Chi Lu, Walid El-Moudani, Téo Cerqueira Revoredo, Felix Mora-Camino. Neural Networks Modelling for Aircraft Flight Guidance Dynamics. Journal of Aerospace Technology and Management, 2012, 4 (2), pp 169-174. ⟨10.5028/jatm.v4i2.152⟩. ⟨hal-01002817⟩
136 Consultations
347 Téléchargements

Altmetric

Partager

Gmail Facebook Twitter LinkedIn More