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Active Control of Wind-Tunnel Model Aeroelastic Response Using Neural NetworksNASA Langley Research Center, Hampton, VA 23681 Under a joint research and development effort conducted by the National Aeronautics and Space Administration and The Boeing Company (formerly McDonnell Douglas) three neural-network based control systems were developed and tested. The control systems were experimentally evaluated using a transonic wind-tunnel model in the Langley Transonic Dynamics Tunnel. One system used a neural network to schedule flutter suppression control laws, another employed a neural network in a predictive control scheme, and the third employed a neural network in an inverse model control scheme. All three of these control schemes successfully suppressed flutter to or near the limits of the testing apparatus, and represent the first experimental applications of neural networks to flutter suppression. This paper will summarize the findings of this project.
Document ID
20040086574
Acquisition Source
Langley Research Center
Document Type
Conference Paper
Authors
Scott, Robert C.
(NASA Langley Research Center Hampton, VA, United States)
Date Acquired
September 7, 2013
Publication Date
March 1, 2000
Subject Category
Aircraft Design, Testing And Performance
Report/Patent Number
SPIE Paper 3991-30
Report Number: SPIE Paper 3991-30
Distribution Limits
Public
Copyright
Work of the US Gov. Public Use Permitted.
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