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- W2044299085 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." @default.
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- W2044299085 date "2008-01-01" @default.
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- W2044299085 title "MultiobjectiveWorst-Case Analysis of a Re-Entry Vehicle Control Law" @default.
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- W2044299085 doi "https://doi.org/10.3182/20080706-5-kr-1001.00427" @default.
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