Multi-objective optimisation under uncertainty with unscented temporal finite elements

Lorenzo Angelo Ricciardi, Christie Maddock, Massimiliano Vasile

Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)peer-review

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Abstract

This paper presents a novel method for multi-objective optimisation under uncertainty developed to study a range of mission trade-offs, and the impact of uncertainties on the evaluation of launch system mission designs. A memetic multi-objective optimisation algorithm, named MODHOC, which combines the Direct Finite Elements in Time transcription method with Multi Agent Collaborative Search, is extended to account for model uncertainties. An Unscented Transformation is used to capture the first two statistical moments of the quantities of interest. A quantification model of the uncertainty was developed for the atmospheric model parameters. An optimisation under uncertainty was run for the design of descent trajectories for a spaceplane-based two-stage launch system.
Original languageEnglish
Title of host publicationEvolutionary Algorithms in Engineering Design Optimization
EditorsDavid Greiner, Antonio Gaspar-Cunha, Daniel Hernández-Sosa, Edmondo Minisci, Aleš Zamuda
Place of PublicationBasel
PublisherMDPI Multidisciplinary Digital Publishing Institute
Pages187-208
Number of pages22
ISBN (Electronic)9783036527154
ISBN (Print)9783036527147
DOIs
Publication statusPublished - 1 Mar 2022

Keywords

  • optimal control
  • multi-objective optimisation
  • robust design
  • trajectory optimisation
  • uncertainty quantification
  • unscented transformation
  • spaceplanes
  • space systems
  • launchers

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