Raol, JR (1996) Feed forward neural networks for aerodynamic modelling and sensor failure detection. In: 47th Annual General Meeting of the Aeronautical Society of India, 6-8 Jan 1996, Madras, India.
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Abstract
In this paper, applications of feed forward 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: | Conference or Workshop Item (Paper) |
|---|---|
| Uncontrolled Keywords: | Mathematical models;Aeronautics;Neural networks; Aerodynamics;Failure;Algorithms;Sensors;Computer simulation; Networks;Feed forward;Least squares method;Polycarbonates; Aircraft; Aircraft instruments;Failure detection;Aerodynamic coefficients;Sensors;Neural nets |
| Subjects: | AERONAUTICS > Aerodynamics |
| Division/Department: | Flight Mechanics and Control Division |
| Depositing User: | M/S ICAST NAL |
| Date Deposited: | 28 Feb 2008 |
| Last Modified: | 07 Jun 2010 16:04 |
| URI: | http://nal-ir.nal.res.in/id/eprint/4366 |
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