Deterministic versus evolutionary optimisation methods for nonlinear robustness analysis of flight control laws

Prathyush Menon, Declan Bates, Ian Postlethwaite

    Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

    2 Citations (Scopus)

    Abstract

    This paper considers the application of two different global optimisation approaches to the problem of analysing the robustness (flight clearance) of nonlinear flight control systems. The analysis employs a typical nonlinear clearance criterion used by the European aerospace industry together with a detailed simulation model of a high performance aircraft with a full authority control law. The deterministic optimisation algorithm used in the study is Dividing RECTangles (DIRECT), while the evolutionary algorithm is Differential Evolution. Both algorithms are hybridised with local gradient- based optimisation methods to improve convergence rates near the global solution. The reliability, computational complexity and efficiency of the two approaches are compared for this realistic engineering example, and the prospects for application of optimisation-based methods in the industrial flight clearance process are discussed.
    Original languageEnglish
    Title of host publication2007 IEEE Congress on Evolutionary Computation
    Place of PublicationPiscataway, NJ
    PublisherIEEE
    Pages1910-1917
    ISBN (Print)978-1424413393
    DOIs
    Publication statusPublished - 2007
    EventIEEE Congress on Evolutionary Computation, 2007. CEC 2007 - Singapore
    Duration: 1 Jan 2007 → …

    Conference

    ConferenceIEEE Congress on Evolutionary Computation, 2007. CEC 2007
    Period1/01/07 → …

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