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dc.contributor.advisorBurl, Jeff B.
dc.contributor.authorSegura, Clement M.
dc.date1990-06
dc.date.accessioned2013-08-01T21:15:20Z
dc.date.available2013-08-01T21:15:20Z
dc.date.issued1990-06
dc.identifier.urihttp://hdl.handle.net/10945/34826
dc.description.abstractThis 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.urihttp://archive.org/details/anrtificialneura1094534826
dc.format.extentv, 71 p. ill.en_US
dc.languageen_US
dc.publisherMonterey, California: Naval Postgraduate Schoolen_US
dc.rightsThis 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.lcshSpace vehicles.en_US
dc.titleAn artificial neural network control system for spacecraft attitude stabilizationen_US
dc.typeThesisen_US
dc.contributor.secondreaderCristi, Roberto.
dc.contributor.corporateNaval Postgraduate School (U.S.)
dc.contributor.departmentElectrical Engineering
dc.subject.authorNeural Networksen_US
dc.subject.authorAttitude Stabilizationen_US
dc.subject.authorPattern Matching Trainingen_US
dc.subject.authorTime-Optimal Control Lawen_US
dc.subject.authorPerformance Index Trainingen_US
dc.description.serviceLieutenant, United States Navyen_US
etd.thesisdegree.nameM.S. in Electrical Engineeringen_US
etd.thesisdegree.levelMastersen_US
etd.thesisdegree.disciplineElectrical Engineeringen_US
etd.thesisdegree.grantorNaval Postgraduate Schoolen_US
dc.description.distributionstatementApproved for public release; distribution is unlimited.


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