Discrete modelling of continuous-time systems having interval uncertainties using genetic algorithms

Chen Chien Hsu*, Tsung Chi Lu, Heng Chou Chen

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


In this paper, an evolutionary approach is proposed to obtain a discrete-time state-space interval model for uncertain continuoustime 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.

Original languageEnglish
Pages (from-to)357-364
Number of pages8
JournalIEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
Issue number1
Publication statusPublished - 2008
Externally publishedYes


  • Discrete modeling
  • Discretization
  • Genetic algorithms
  • Interval plant
  • Model conversion
  • Sampled-data systems
  • Uncertain continuous-time systems

ASJC Scopus subject areas

  • Signal Processing
  • Computer Graphics and Computer-Aided Design
  • Electrical and Electronic Engineering
  • Applied Mathematics


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