Robust trajectory optimisation of a TSTO spaceplane using uncertainty-based aerodynamic models

Ricciardi, L., Maddock, C. and Vasile, M. (2020) Robust trajectory optimisation of a TSTO spaceplane using uncertainty-based aerodynamic models. In: 23rd AIAA International Space Planes and Hypersonics Systems and Technologies Conference, Montréal, Québec, Canada [Event cancelled], 10-12 March 2020, ISBN 9781624106002 (doi: 10.2514/6.2020-2403)

195937.pdf - Accepted Version



This paper presents a multi-objective trajectory optimisation under uncertainty for the ascent of a two-stage, semi-reusable space launch system. Using Orbital Access' Orbital 500-R launcher as a test case, robust multi-disciplinary design optimisation is used to analyse the trade-offs with both the vehicle and system design, and operation. An area of focus is on the predicted performance and its impact on the design and planned mission scenarios. The atmospheric model uncertainties are quantified for the atmospheric surrogate model and integrated into the optimal control solver MODHOC, extended by the addition of an unscented transformation to handle the uncertainties. A multi-objective optimisation under uncertainty is run, examining the Pareto-optimal sets for the ascent trajectory and vehicle design.

Item Type:Conference Proceedings
Additional Information:This work has been partially funded by the UK Space Agency and European Space Agency (ESA) General Support Technology Programme (GSTP) De-Risking Call 2017/18, ESA RFP/2-1690/18/NL/BJ/zk.
Glasgow Author(s) Enlighten ID:Vasile, Dr Massimiliano
Authors: Ricciardi, L., Maddock, C., and Vasile, M.
College/School:College of Science and Engineering > School of Engineering > Autonomous Systems and Connectivity
Copyright Holders:Copyright © by Christie Maddock, Massimiliano Vasile, Lorenzo Ricciardi
First Published:First published in 23rd AIAA International Space Planes and Hypersonic Systems and Technologies Conference 2020
Publisher Policy:Reproduced in accordance with the publisher copyright policy

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