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Neural Network for Positioning Space Station Solar ArraysAs a shuttle approaches the Space Station Freedom for a rendezvous, the shuttle's reaction control jet firings pose a risk of excessive plume impingement loads on Freedom solar arrays. The current solution to this problem, in which the arrays are locked in a feathered position prior to the approach, may be neither accurate nor robust, and is also expensive. An alternative solution is proposed here: the active control of Freedom's beta gimbals during the approach, positioning the arrays dynamically in such a way that they remain feathered relative to the shuttle jet most likely to cause an impingement load. An artificial neural network is proposed as a means of determining the gimbal angles that would drive plume angle of attack to zero. Such a network would be both accurate and robust, and could be less expensive to implement than the current solution. A network was trained via backpropagation, and results, which compare favorably to the current solution as well as to some other alternatives, are presented. Other training options are currently being evaluated.
Document ID
19940032436
Acquisition Source
Legacy CDMS
Document Type
Conference Paper
Authors
Graham, Ronald E.
(NASA Lewis Research Center Cleveland, OH, United States)
Lin, Paul P.
(NASA Lewis Research Center Cleveland, OH, United States)
Date Acquired
September 6, 2013
Publication Date
June 1, 1994
Subject Category
Engineering (General)
Report/Patent Number
NASA-TM-106656
NAS 1.15:106656
E-8969
Meeting Information
Meeting: Symposium on Automatic Control in Aerospace
Location: Palo Alto, CA
Country: United States
Start Date: September 12, 1994
End Date: September 16, 1994
Sponsors: International Federation of Automatic Control
Accession Number
94N36943
Distribution Limits
Public
Copyright
Work of the US Gov. Public Use Permitted.
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