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Performance Comparison of Genetic and Tabu Search Algorithms for System Identification

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Knowledge-Based Intelligent Information and Engineering Systems (KES 2006)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4251))

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Abstract

This paper presents a performance comparison of the genetic and tabu search algorithm for system identification operations of different processes. The identification procedure is based on open-loop step response analysis of the processes. Each of the two algorithms is applied to determine the optimal parameter values of the processes to be modelled. Simulation results demonstrated that the presented algorithms can be efficiently used in the identification problems.

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Author information

Authors and Affiliations

  1. Dept. of Electronic Eng., Erciyes University, 38039, Kayseri, Turkey

    Aytekin Bagis

Authors
  1. Aytekin Bagis
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Editor information

Editors and Affiliations

  1. School of Design, Engineering and Computing, Bournemouth University, UK

    Bogdan Gabrys

  2. Centre for SMART Systems, School of Environment and Technology, University of Brighton, BN2 4GJ, Brighton, UK

    Robert J. Howlett

  3. School of Electrical and Information Engineering, Knowledge Based Intelligent Engineering Systems Centre, University of South Australia, Mawson Lakes, 5095, SA, Australia

    Lakhmi C. Jain

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© 2006 Springer-Verlag Berlin Heidelberg

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Bagis, A. (2006). Performance Comparison of Genetic and Tabu Search Algorithms for System Identification. In: Gabrys, B., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2006. Lecture Notes in Computer Science(), vol 4251. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11892960_12

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  • DOI: https://doi.org/10.1007/11892960_12

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-46535-5

  • Online ISBN: 978-3-540-46536-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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