Neural Network for Positioning Space Station Solar Arrays
- Author
- Graham, Ronald E.
- Published
- Jun 1, 1994.
- Physical Description
- 1 electronic document
- Additional Creators
- Lin, Paul P.
Online Version
- hdl.handle.net , Connect to this object online.
- Restrictions on Access
- Unclassified, Unlimited, Publicly available.
Free-to-read Unrestricted online access - Summary
- As 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.
- Other Subject(s)
- Collection
- NASA Technical Reports Server (NTRS) Collection.
- Note
- Document ID: 19940032436.
Accession ID: 94N36943.
E-8969.
NAS 1.15:106656.
NASA-TM-106656.
Symposium on Automatic Control in Aerospace; 12-16 Sep. 1994; Palo Alto, CA; United States. - Terms of Use and Reproduction
- No Copyright.
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