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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/60931


    Title: Discrete Modelling of Continuous-Time Systems Having Interval Uncertainties Using Genetic Algorithms
    Authors: 許陳鑑
    Contributors: 淡江大學電機工程學系
    Keywords: discrete modelling;genetic algorithms;uncertain continuous-time systems;interval plant;discretization;model conversion;sampled-data systems
    Date: 2008-01
    Issue Date: 2011-10-15 01:06:42 (UTC+8)
    Publisher: Tokyo: Denshi Jouhou Tsuushin Gakkai
    Abstract: In this paper, an evolutionary approach is proposed to obtain a discrete-time state-space interval model for uncertain continuous-time systems having interval uncertainties. Based on a worst-case analysis, the problem to derive the discrete interval model is first formulated as multiple mono-objective optimization problems for matrix-value functions associated with the discrete system matrices, and subsequently optimized via a proposed genetic algorithm (GA) to obtain the lower and upper bounds of the entries in the system matrices. To show the effectiveness of the proposed approach, roots clustering of the characteristic equation of the obtained discrete interval model is illustrated for comparison with those obtained via existing methods.
    Relation: IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences E91-A(1), pp.357-364
    DOI: 10.1093/ietfec/e91-a.1.357
    Appears in Collections:[Graduate Institute & Department of Electrical Engineering] Journal Article

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