Active Control of Wind-Tunnel Model Aeroelastic Response Using Neural Networks

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Abstract
Under a joint research and development effort conducted by NASA 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 NASA Langley Research Center Transonic Dynamics Tunnel, One system used a neural network to schedule Butter 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 Butter suppression. The findings of this project are summarized.

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