Multiobjective worst-case analysis of a re-entry vehicle control law

Menon, Prathyush, Postlethwaite, Ian, Bennani, Samir and Bates, Declan (2008) Multiobjective worst-case analysis of a re-entry vehicle control law. In: 17th IFAC World Congress, 6-11 July 2008, South Korea.

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Official URL: http://dx.doi.org/10.3182/20080706-5-KR-1001.00427

Abstract

This paper reports results of a joint study between ESA and the University of Leicester on worst-case analysis of NDI control laws for an industrial standard Reusable Launch Vehicle. Multiple performance objectives over a particular phase of the atmospheric re-entry are considered simultaneously in the analysis, yielding valuable information about the trade-offs involved in satisfying different clearance criteria. Two different multiobjective optimisation algorithms are employed to identify the pareto front of the multiple performance objectives. In the initial analysis, a fast, elitist, evolutionary multiobjective optimisation algorithm known as nondominated sorting genetic algorithm (NSGA-II) is employed. A hybrid multi objective optimisation algorithm which adaptively switches between three different strategies such as NSGA-II, differential evolution and the metropolis algorithm, is also developed and applied to the clearance problem. The results of our analysis show that the proposed optimisation-based approach has the potential to significantly improve both the reliability and efficiency of the flight clearance process for future re-entry vehicles.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: aerospace applications, evolutionary algorithms, robustness analysis
Subjects: H600 Electronic and Electrical Engineering
Department: Faculties > Engineering and Environment > Mathematics and Information Sciences
Depositing User: Sarah Howells
Date Deposited: 29 Oct 2012 15:12
Last Modified: 10 Aug 2015 11:31
URI: http://nrl.northumbria.ac.uk/id/eprint/10090

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