Approximation methods for quick evaluation of invariant manifolds during global optimization

Ryne Beeson, Devin Bunce, Victoria Coverstone

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Scopus citations

Abstract

The purpose of this paper is to explore potential methods for improving approximation methods of invariant manifolds. The ultimate goal is to produce a set of methods and algorithms that can then be used for rapid evaluation of the invariant manifolds within a global optimization framework. Implemented algorithms must be computationally efficient in terms of both memory storage and execution and provide reasonable accuracy. The techniques explored in this paper build around a baseline cubic convolution method and include analysis of energy projection, polar parameterization, marginalization (integration), linear, fourth-order, and a one-dimension optimal parameter exploration. The result is new insight into the development of efficient and accurate approximation methods, which tend to show that a mix of the above methods could be used to build a better method than baseline cubic convolution.

Original languageEnglish (US)
Title of host publicationAIAA/AAS Astrodynamics Specialist Conference, 2016
PublisherAmerican Institute of Aeronautics and Astronautics Inc, AIAA
ISBN (Print)9781624104459
StatePublished - Jan 1 2016
Externally publishedYes
EventAIAA/AAS Astrodynamics Specialist Conference, 2016 - Long Beach, United States
Duration: Sep 13 2016Sep 16 2016

Publication series

NameAIAA/AAS Astrodynamics Specialist Conference, 2016

Other

OtherAIAA/AAS Astrodynamics Specialist Conference, 2016
CountryUnited States
CityLong Beach
Period9/13/169/16/16

ASJC Scopus subject areas

  • Astronomy and Astrophysics
  • Aerospace Engineering

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