JPL Technical Report Server

Evolutionary computing for low-thrust navigation

Show simple item record

dc.contributor.author Lee, Seungwon
dc.contributor.author Fink, Wolfgang
dc.contributor.author von Allmed, Paul
dc.contributor.author Petropoulos, Anastassios E.
dc.contributor.author Russell, Ryan P.
dc.contributor.author Terrile, Richard J.
dc.date.accessioned 2006-08-16T18:16:26Z
dc.date.available 2006-08-16T18:16:26Z
dc.date.issued 2005-08-30
dc.identifier.citation AIAA Space Conference, Long Beach, California, August 31 - September 01, 2005. en
dc.identifier.clearanceno 05-2434
dc.identifier.uri http://hdl.handle.net/2014/39674
dc.description.abstract The development of new mission concepts requires efficient methodologies to analyze, design and simulate the concepts before implementation. New mission concepts are increasingly considering the use of ion thrusters for fuel-efficient navigation in deep space. This paper presents parallel, evolutionary computing methods to design trajectories of spacecraft propelled by ion thrusters and to assess the trade-off between delivered payload mass and required flight time. The developed methods utilize a distributed computing environment in order to speed up computation, and use evolutionary algorithms to find globally Pareto-optimal solutions. The methods are coupled with two main traditional trajectory design approaches, which are called direct and indirect. en
dc.description.sponsorship NASA/JPL en
dc.format.extent 1958336 bytes
dc.format.mimetype application/pdf
dc.language.iso en_US en
dc.publisher Pasadena, CA : Jet Propulsion Laboratory, National Aeronautics and Space Administration, 2005. en
dc.subject evolutionary computing en
dc.subject low thrust navigations en
dc.subject optimization en
dc.title Evolutionary computing for low-thrust navigation en
dc.type Preprint en


Files in this item

This item appears in the following Collection(s)

Show simple item record

Search


Browse

My Account