Feed forward neural networks for aerodynamic modelling and sensor failure detection

Raol, JR (1995) Feed forward neural networks for aerodynamic modelling and sensor failure detection. Aeronautical Society of India, Journal, 47 (4). pp. 193-199. ISSN 0001-9267

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Abstract

In this paper, applications of feedforward neural networks for aerodynamic modelling and sensor failure detection are studied.These networks are trained using fast back propagation recursive least squares algorithms with forgetting factors. Specifically,three training algorithms are implemented in PC MATLAB. The numerical results are presented using a simulation of aircraft mathematical models.

Item Type: Journal Article
Uncontrolled Keywords: Mathematical models;Aeronautics;Neural networks; Aerodynamics;Failure;Algorithms;Sensors;Computer simulation; Networks;Feedforward;Least squares method;Polycarbonates; Aircraft;Training;Aircraft instruments;Failure detection;Aerodynamic coefficients;Sensors;Neural nets
Subjects: AERONAUTICS > Aircraft Design, Testing & Performance
Division/Department: Flight Mechanics and Control Division
Depositing User: M/S ICAST NAL
Date Deposited: 02 Jan 2008
Last Modified: 24 May 2010 09:55
URI: http://nal-ir.nal.res.in/id/eprint/4364

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