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.

Full text not available from this repository. (Request a copy)

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, Physics and Electrical Engineering
Depositing User:	Sarah Howells
Date Deposited:	29 Oct 2012 15:12
Last Modified:	13 Oct 2019 00:24
URI:	http://nrl.northumbria.ac.uk/id/eprint/10090

Downloads