Multiobjective optimization using variable complexity modelling for control system design

Valceres V R Silva*, Peter J. Fleming, Jungiro Sugimoto, Ryuichi Yokoyama

*この研究の対応する著者

    研究成果: Article査読

    22 被引用数 (Scopus)

    抄録

    A multi-stage design approach that uses a multiobjective genetic algorithm as the framework for optimization and multiobjective preference articulation, and an H_infty loop-shaping technique are used to design controllers for a gas turbine engine. A non-linear model is used to assess performance of the controller. Because the computational load of applying multiobjective genetic algorithm to this control strategy is very high, a neural network and response surface models are used in order to speed up the design process within the framework of a multiobjective genetic algorithm. The final designs are checked using the original non-linear model.

    本文言語English
    ページ(範囲)392-401
    ページ数10
    ジャーナルApplied Soft Computing Journal
    8
    1
    DOI
    出版ステータスPublished - 2008 1月

    ASJC Scopus subject areas

    • ソフトウェア
    • コンピュータ サイエンスの応用
    • 人工知能

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