A Markovian State-Space Flexibility Framework Applied to Distributed-Payload Satellite Design Decisions

Author(s)
Lafleur, Jarret M.
Advisor(s)
Editor(s)
Associated Organization(s)
Organizational Unit
Daniel Guggenheim School of Aerospace Engineering
The Daniel Guggenheim School of Aeronautics was established in 1931, with a name change in 1962 to the School of Aerospace Engineering
Series
Supplementary to:
Abstract
Over the past decade, the space industry has increasingly recognized the need for new systems to be designed for flexibility, or the capability to be easily modified in response to changes in future requirements or environments. Despite widespread interest, however, the state of the art in designing flexibility into space systems today remains limited. To address these limitations, this paper presents the basis of a quantitative, stochastic, multi-objective, and multi-period framework for integrating flexibility into space system design decisions. Central to the framework are five steps that (1) define configuration options and transition costs, (2) define a stochastic model for mission demand environment changes, (3) link configurations and demand environments via quantitative performance metrics, (4) identify Pareto-optimal configuration paths and decision policies, taking advantage of efficient multi objective Markov decision process techniques, and (5) utilize these path and policy results to inform initial system selection. The framework is applied to a realistic example in which design decisions are suggested for a hypothetical multi- or distributed-payload satellite system. The application illustrates how flexibility-informed trades can permit selection of a satellite system that most effectively responds to uncertain future demands.
Sponsor
Date
2011-09
Extent
Resource Type
Text
Resource Subtype
Paper
Rights Statement
Unless otherwise noted, all materials are protected under U.S. Copyright Law and all rights are reserved