J. Aerosp. Technol. Manag. vol.4 número2

INTRODUCTION

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Neural Networks Modelling for Aircraft Flight Guidance

Dynamics

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Abstract: The sustained increase of the air transportation sector over the last decades has led to traffic satu-rated 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 f light dynamics, which are essentially nonlinear, appears necessary. Aircraft f light dynamics is shown to be differentially f lat, 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 f light dynamics this differential f latness 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.

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Neural network

Trajectory generation

Flight dynamics Auto pilot

Fast control feedback

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Neural inversion of flight mechanics

Aircraft attitude and thrust

Receiver position

Sound exposure level computation

Sound exposure level Aircraft trajectory

and position