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The Application of Neural Networks for Spin Avoidance and Recovery
Technical Paper
1999-01-5612
ISSN: 0148-7191, e-ISSN: 2688-3627
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English
Abstract
This paper presents a method by which artificial neural networks can be trained and used to identify a possible spin entry, differentiate between an incipient spin and a stabilized spin, and predict required recovery controls. These were then implemented into a simulation and tested using data from actual flight tests conducted by NASA Langley Research Center, to verify that artificial neural networks can successfully be used for this application. The spin avoidance and recovery system functioned properly. In addition, a weighting system was developed to predict possible spin characteristics of aircraft, depending on the relative magnitude of the three principal moments of inertia.
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Authors
Citation
Lay,, L., Nagati, M., and Steck, J., "The Application of Neural Networks for Spin Avoidance and Recovery," SAE Technical Paper 1999-01-5612, 1999, https://doi.org/10.4271/1999-01-5612.Also In
References
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