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dc.contributor.authorShirazi, A. 
dc.contributor.authorCeberio, J.
dc.contributor.authorLozano, J.A. 
dc.date.accessioned2017-06-19T14:21:05Z
dc.date.available2017-06-19T14:21:05Z
dc.date.issued2017-06-06
dc.identifier.isbn978-1-5090-0623-6
dc.identifier.urihttp://hdl.handle.net/20.500.11824/683
dc.description.abstractIn space environment, perturbations make the spacecraft lose its predefined orbit in space. One of these undesirable changes is the in-plane rotation of space orbit, denominated as orbital precession. To overcome this problem, one option is to correct the orbit direction by employing low-thrust trajectories. However, in addition to the orbital perturbation acting on the spacecraft, a number of parameters related to the spacecraft and its propulsion system must be optimized. This article lays out the trajectory optimization of orbital precession missions using Evolutionary Algorithms (EAs). In this research, the dynamics of spacecraft in the presence of orbital perturbation is modeled. The optimization approach is employed based on the parametrization of the problem according to the space mission. Numerous space mission cases have been studied in low and middle Earth orbits, where various types of orbital perturbations are acted on spacecraft. Consequently, several EAs are employed to solve the optimization problem. Results demonstrate the practicality of different EAs, along with comparing their convergence rates. With a unique trajectory model, EAs prove to be an efficient, reliable and versatile optimization solution, capable of being implemented in conceptual and preliminary design of spacecraft for orbital precession missions.en_US
dc.description.sponsorshipIT-609-13 2013-2018, TIN2016-78365-Ren_US
dc.formatapplication/pdfen_US
dc.language.isoengen_US
dc.rightsReconocimiento-NoComercial-CompartirIgual 3.0 Españaen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/3.0/es/en_US
dc.subjectAerospace Engineeringen_US
dc.subjectEvolutionary Algorithmen_US
dc.subjectOptimizationen_US
dc.subjectSpacecraften_US
dc.subjectOrbital Precessionen_US
dc.subjectGenetic Algorithmen_US
dc.subjectParticle Swarm Optimizationen_US
dc.subjectEstimation of Distribution Algorithmsen_US
dc.subjectLow-thrusten_US
dc.titleEvolutionary algorithms to optimize low-thrust trajectory design in spacecraft orbital precession missionen_US
dc.typeinfo:eu-repo/semantics/conferenceObjecten_US
dc.relation.projectIDES/1PE/SEV-2013-0323en_US
dc.relation.projectIDEUS/BERC/BERC.2014-2017en_US
dc.rights.accessRightsinfo:eu-repo/semantics/openAccessen_US
dc.type.hasVersioninfo:eu-repo/semantics/acceptedVersionen_US
dc.journal.titleIEEE Congress on Evolutionary Computationen_US


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Reconocimiento-NoComercial-CompartirIgual 3.0 España
Except where otherwise noted, this item's license is described as Reconocimiento-NoComercial-CompartirIgual 3.0 España