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System Identification Using Genetic Algorithms

  • Jana Nowaková
  • Miroslav Pokorný
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 303)

Abstract

System identification is one of the necessary tasks in controller design and its adaptation. Many identification methods are known, and new ones are still being developed in order to find a better solution for huge scale of cases. In the paper identification of system of 2nd order systems using genetic algorithms is demonstrated. In presented case genetic algorithms are used for finding parameters of difference equation of the controlled system and it substitutes classic, conventional optimization methods. Proposed method can be used for continuous identification or it can be activated in defined time points on stored data. And on the other hand, presented task is also a case of a specific usage of genetic algorithms and it can serve as a proof of efficiency of this non-conventional optimization method (simulated in the Matlab&Simulink software environment).

Keywords

Identification system genetic algorithms optimization 

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References

  1. 1.
    Friedland, B.: Advanced control system design. Prentice-Hall, USA (1996)MATHGoogle Scholar
  2. 2.
    Keesman, K.J.: System Identification. Springer, London (2011)CrossRefMATHGoogle Scholar
  3. 3.
    Goldberg, D., Sastry, K.: Genetic Algorithms. The design of Innovation. Springer, NY (2007)Google Scholar
  4. 4.
    Levine, W.S.: The Control Handbook. Jaico Publishing House, Mumbai (1999)Google Scholar
  5. 5.
    El Attar, R.: Lecture Notes on Z-Transform. Lulu.com, USA (2006)Google Scholar
  6. 6.
    Ajith, A., Solar, J.R., Koppen, M.: Soft Computing Systems Design, Management and Application. IOS Press, The Netherlands (2002)Google Scholar
  7. 7.
    Garnier, H., Wang, L.: Identification of Continuous-time Models from Sampled Data. Springer, London (2008)CrossRefGoogle Scholar
  8. 8.
    Nowaková, J., Pokorný, M.: On PID Controller Design Using Knowledge Based Fuzzy System. from Sampled Data. Advances in Electrical and Electronic Engineering 10(1), 18–27 (2012)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.Faculty of Electrical Engineering and Computer Science, Department of Cybernetics and Biomedical EngineeringVŠB-Technical University of OstravaOstravaCzech Republic

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