IDENTIFICATION OF AERODYNAMIC COEFFICIENTS USING COMPUTATIONAL NEURALNETWORKS

Citation
Dj. Linse et Rf. Stengel, IDENTIFICATION OF AERODYNAMIC COEFFICIENTS USING COMPUTATIONAL NEURALNETWORKS, Journal of guidance, control, and dynamics, 16(6), 1993, pp. 1018-1025
Citations number
25
Language
INGLESE
art.tipo
Article
Categorie Soggetti
Instument & Instrumentation","Aerospace Engineering & Tecnology
ISSN journal
0731-5090
Volume
16
Issue
6
Year of publication
1993
Pages
1018 - 1025
Database
ISI
SICI code
0731-5090(1993)16:6<1018:IOACUC>2.0.ZU;2-X
Abstract
Precise, smooth aerodynamic models are required for implementing adapt ive, nonlinear control strategies. Accurate representations of aerodyn amic coefficients can be generated for the complete flight envelope by combining computational neural network models with an estimation-befo re-modeling paradigm for on-line training information. A novel method of incorporating first partial derivative information is employed to e stimate the weights in individual feedforward neural networks for each aerodynamic coefficient. The method is demonstrated by generating a m odel of the normal force coefficient of a twin-jet transport aircraft from simulated flight data, and promising results are obtained.