The feasibility of neural networks to control dynamic systems is examined. Control of a one-dimensional problem is initially investigated to develop an understanding of the structure and simulation of the neural networks. A nondimensional problem is also explored to apply a single neural network design to controlling a class of systems with a wide variety of modeling parameters. Finally, these techniques are applied to control a space vehicle to transfer, intercept, and rendezvous with another orbiting vehicle using the Clohessy-Wiltshire equations of relative motion in two dimensions. A combination of open-loop and closed-loop neural network controllers is shown to work effectively for this problem. Noise is added to the neural network inputs to demonstrate the robustness of these networks. / Ph. D.
Identifer | oai:union.ndltd.org:VTETD/oai:vtechworks.lib.vt.edu:10919/38160 |
Date | 06 June 2008 |
Creators | Youmans, Elisabeth A. |
Contributors | Aerospace Engineering, Lutze, Frederick H., Durham, Wayne C., Cliff, Eugene M., Anderson, Mark R., VanLandingham, Hugh F. |
Publisher | Virginia Tech |
Source Sets | Virginia Tech Theses and Dissertation |
Language | English |
Detected Language | English |
Type | Dissertation, Text |
Format | xiii, 186 leaves, BTD, application/pdf, application/pdf |
Rights | In Copyright, http://rightsstatements.org/vocab/InC/1.0/ |
Relation | OCLC# 34091638, LD5655.V856_1995.Y686.pdf |
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