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Reconfigurable Flight Control Design using a Robust Servo LQR and Radial Basis Function Neural NetworksThis viewgraph presentation reviews the use of a Robust Servo Linear Quadratic Regulator (LQR) and a Radial Basis Function (RBF) Neural Network in reconfigurable flight control designs in adaptation to a aircraft part failure. The method uses a robust LQR servomechanism design with model Reference adaptive control, and RBF neural networks. During the failure the LQR servomechanism behaved well, and using the neural networks improved the tracking.
Document ID
20090008513
Acquisition Source
Armstrong Flight Research Center
Document Type
Conference Paper
Authors
Burken, John J.
(NASA Dryden Flight Research Center Edwards, CA, United States)
Date Acquired
August 24, 2013
Publication Date
July 31, 2005
Subject Category
Aircraft Stability And Control
Report/Patent Number
DFRC-454
Report Number: DFRC-454
Meeting Information
Meeting: International Joint Conference on Neural Networks (IJCNN 2005)
Location: Montreal
Country: Canada
Start Date: August 1, 2005
End Date: August 5, 2005
Distribution Limits
Public
Copyright
Work of the US Gov. Public Use Permitted.
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