Actions for System Design under Uncertainty : Evolutionary Optimization of the Gravity Probe-B Spacecraft

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System Design under Uncertainty : Evolutionary Optimization of the Gravity Probe-B Spacecraft

Author
Parkinson, Bradford W.
Published
[1994].
Physical Description
1 electronic document
Additional Creators
Pullen, Samuel P.
Online Version

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Unclassified, Unlimited, Publicly available.
Free-to-read Unrestricted online access
Summary
This paper discusses the application of evolutionary random-search algorithms (Simulated Annealing and Genetic Algorithms) to the problem of spacecraft design under performance uncertainty. Traditionally, spacecraft performance uncertainty has been measured by reliability. Published algorithms for reliability optimization are seldom used in practice because they oversimplify reality. The algorithm developed here uses random-search optimization to allow us to model the problem more realistically. Monte Carlo simulations are used to evaluate the objective function for each trial design solution. These methods have been applied to the Gravity Probe-B (GP-B) spacecraft being developed at Stanford University for launch in 1999, Results of the algorithm developed here for GP-13 are shown, and their implications for design optimization by evolutionary algorithms are discussed.
Other Subject(s)
Collection
NASA Technical Reports Server (NTRS) Collection.
Note
Document ID: 19960048670.
Accession ID: 96N33891.
NAS 1.26:202084.
NASA-CR-202084.
Parallel Problem Solving from Nature Conference; 9-14 Oct. 1994; Jerusalem; Israel.
Terms of Use and Reproduction
No Copyright.
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