Due to the various benefits it offers, flight simulation now is an essential part of aircraft development and exploitation. The basis of any flight simulation is the mathematical model of the aircraft to be simulated. Several modeling and identification techniques have been applied to aircraft identification with satisfying results. In recent years, artificial neural networks have proven to be a promising tool for modeling of nonlinear systems. In this final thesis will be shown that neural networks can succesfully be applied to the identification of nonlinear aerodynamic aircraft models.
Neural Networks for Aerodynamic Aircraft Modelling
1996
104 pages
Report
No indication
English
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