Discrete modeling of uncertain continuous systems having an interval structure using genetic algorithms

Chen Chien Hsu, Shih Chi Chang, Hsin Yen Kuo

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, an evolutionary approach is proposed to obtain the discrete-time transfer function for uncertain continuous-time systems having interval uncertainties. Based on a worst-case analysis, the problem to derive the discrete-time model is first formulated as multiple mono-objective optimization problems for coefficients in the discrete model, and subsequently minimized and maximized via a proposed genetic algorithm to obtain the lower and upper bounds of the coefficient functions. The problem of non-linearly coupled coefficients with exponential nature occurred in the exact discrete-time transfer function is therefore circumvented while preserving the interval structure in the resulting discrete model by using this approach. Because of the time-consuming process that genetic algorithms generally exhibit, particularly the problem nature which requires undertaking a large number of evolution processes, parallel computation for the proposed evolutionary approach in a MATLAB-based working environment is therefore proposed to accelerate the derivation process.

Original languageEnglish
Title of host publicationProceedings of the IASTED International Conference on Computational Intelligence
Pages310-315
Number of pages6
Publication statusPublished - 2005 Dec 1
EventIASTED International Conference on Computational Intelligence - Calgary, AB, Canada
Duration: 2005 Jul 42005 Jul 6

Publication series

NameProceedings of the IASTED International Conference on Computational Intelligence
Volume2005

Other

OtherIASTED International Conference on Computational Intelligence
CountryCanada
CityCalgary, AB
Period05/7/405/7/6

Fingerprint

Genetic algorithms
Transfer functions
Continuous time systems
MATLAB
Uncertainty

Keywords

  • Discrete modeling
  • Discretization
  • Genetic algorithms
  • Interval plant
  • Parallel computation
  • Sampled-data systems
  • Uncertain systems

ASJC Scopus subject areas

  • Engineering(all)

Cite this

Hsu, C. C., Chang, S. C., & Kuo, H. Y. (2005). Discrete modeling of uncertain continuous systems having an interval structure using genetic algorithms. In Proceedings of the IASTED International Conference on Computational Intelligence (pp. 310-315). (Proceedings of the IASTED International Conference on Computational Intelligence; Vol. 2005).

Discrete modeling of uncertain continuous systems having an interval structure using genetic algorithms. / Hsu, Chen Chien; Chang, Shih Chi; Kuo, Hsin Yen.

Proceedings of the IASTED International Conference on Computational Intelligence. 2005. p. 310-315 (Proceedings of the IASTED International Conference on Computational Intelligence; Vol. 2005).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Hsu, CC, Chang, SC & Kuo, HY 2005, Discrete modeling of uncertain continuous systems having an interval structure using genetic algorithms. in Proceedings of the IASTED International Conference on Computational Intelligence. Proceedings of the IASTED International Conference on Computational Intelligence, vol. 2005, pp. 310-315, IASTED International Conference on Computational Intelligence, Calgary, AB, Canada, 05/7/4.
Hsu CC, Chang SC, Kuo HY. Discrete modeling of uncertain continuous systems having an interval structure using genetic algorithms. In Proceedings of the IASTED International Conference on Computational Intelligence. 2005. p. 310-315. (Proceedings of the IASTED International Conference on Computational Intelligence).
Hsu, Chen Chien ; Chang, Shih Chi ; Kuo, Hsin Yen. / Discrete modeling of uncertain continuous systems having an interval structure using genetic algorithms. Proceedings of the IASTED International Conference on Computational Intelligence. 2005. pp. 310-315 (Proceedings of the IASTED International Conference on Computational Intelligence).
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