Neural network control of space vehicle orbit transfer, intercept, and rendezvous maneuvers

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.

Name thesis:degree_name

Ph. D.

Level thesis:degree_level

doctoral

Discipline thesis:degree_discipline

Aerospace Engineering

Department dc:contributor.department

Aerospace Engineering

Grantor dc:publisher

Virginia Tech

Year dc:date.issued

1995

Author dc:creator

• Youmans, Elisabeth A.

Chair dc:contributor.committeechair

• Lutze, Frederick H.

Committee members dc:contributor.committeemember

• Durham, Wayne C.
• Cliff, Eugene M.
• Anderson, Mark R.
• VanLandingham, Hugh F.

• Optimization
• autonomous
• controller

Statement dc:rights

• In Copyright

Licence dc:rights.uri

• http://rightsstatements.org/vocab/InC/1.0/

Language dc:language.iso

en

Dc Identifier Other

etd-06062008-162101

OAI identifier oai:identifier

oai:vtechworks.lib.vt.edu:10919/38160