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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 language | English |
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Article number | 3010 |
Number of pages | 22 |
Journal | Mathematics |
Volume | 9 |
Issue number | 23 |
DOIs | |
Publication status | Published - 24 Nov 2021 |
Keywords
- optimal control
- multi-objective optimisation
- robust design
- trajectory optimisation
- uncertainty quantification
- unscented transformation
- spaceplanes
- space systems
- launchers
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Dive into the research topics of 'Multi-objective optimisation under uncertainty with unscented temporal finite elements'. Together they form a unique fingerprint.Projects
- 1 Finished
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ESA NPI on Multi-Objective Hybrid Optimal Control Problems
Vasile, M. (Principal Investigator)
1/01/15 → 2/03/18
Project: Research - Studentship
Research output
- 2 Citations
- 1 Chapter (peer-reviewed)
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Multi-objective optimisation under uncertainty with unscented temporal finite elements
Ricciardi, L. A., Maddock, C. & Vasile, M., 1 Mar 2022, Evolutionary Algorithms in Engineering Design Optimization. Greiner, D., Gaspar-Cunha, A., Hernández-Sosa, D., Minisci, E. & Zamuda, A. (eds.). Basel: MDPI Multidisciplinary Digital Publishing Institute, p. 187-208 22 p.Research output: Chapter in Book/Report/Conference proceeding › Chapter (peer-reviewed) › peer-review
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