An artificial neural network control system for spacecraft attitude stabilization
dc.contributor.advisor | Burl, Jeff B. | |
dc.contributor.author | Segura, Clement M. | |
dc.date | 1990-06 | |
dc.date.accessioned | 2013-08-01T21:15:20Z | |
dc.date.available | 2013-08-01T21:15:20Z | |
dc.date.issued | 1990-06 | |
dc.identifier.uri | http://hdl.handle.net/10945/34826 | |
dc.description.abstract | This document reports the results of research into the application of artificial neural networks to controlling dynamic systems. The network used is a feed-forward, fully-connected, 3-layer perception. Two methods of training neural networks via error back-propagation were used. Pattern matching training is a direct method that teaches the basic response. Performance index training is a new technique that refines the response. Performance index training is based on the concept of enforced performance. A neural network will learn to meet a specific performance goal if the performance standard is the only solution to a problem. Performance index training is devised to teach the neural network the time-optimal control law for the system. Real-time adaptation of a neural network in closed loop control of the CrewEquipment Retriever was demonstrated in computer simulations. | en_US |
dc.description.uri | http://archive.org/details/anrtificialneura1094534826 | |
dc.format.extent | v, 71 p. ill. | en_US |
dc.language | en_US | |
dc.publisher | Monterey, California: Naval Postgraduate School | en_US |
dc.rights | This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States. | en_US |
dc.subject.lcsh | Space vehicles. | en_US |
dc.title | An artificial neural network control system for spacecraft attitude stabilization | en_US |
dc.type | Thesis | en_US |
dc.contributor.secondreader | Cristi, Roberto. | |
dc.contributor.corporate | Naval Postgraduate School (U.S.) | |
dc.contributor.department | Electrical Engineering | |
dc.subject.author | Neural Networks | en_US |
dc.subject.author | Attitude Stabilization | en_US |
dc.subject.author | Pattern Matching Training | en_US |
dc.subject.author | Time-Optimal Control Law | en_US |
dc.subject.author | Performance Index Training | en_US |
dc.description.service | Lieutenant, United States Navy | en_US |
etd.thesisdegree.name | M.S. in Electrical Engineering | en_US |
etd.thesisdegree.level | Masters | en_US |
etd.thesisdegree.discipline | Electrical Engineering | en_US |
etd.thesisdegree.grantor | Naval Postgraduate School | en_US |
dc.description.distributionstatement | Approved for public release; distribution is unlimited. |
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