Discrete Modelling of Continuous-Time Systems Having Interval Uncertainties Using Genetic Algorithms

Chen-Chien HSU  Tsung-Chi LU  Heng-Chou CHEN  

IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences   Vol.E91-A   No.1   pp.357-364
Publication Date: 2008/01/01
Online ISSN: 1745-1337
DOI: 10.1093/ietfec/e91-a.1.357
Print ISSN: 0916-8508
Type of Manuscript: PAPER
Category: Systems and Control
discrete modelling,  genetic algorithms,  uncertain continuous-time systems,  interval plant,  discretization,  model conversion,  sampled-data systems,  

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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.