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Evolutionary Control of CML Systems

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Book cover Evolutionary Algorithms and Chaotic Systems

Part of the book series: Studies in Computational Intelligence ((SCI,volume 267))

Abstract

This chapter is a continuation of an investigation on deterministic spatiotemporal chaos real-time control by means of selected evolutionary techniques. Real-time like behavior is specially defined and simulated with spatiotemporal chaos model based on mutually nonlineary joined n equations, so called Coupled Map Lattices. In total five evolutionary algorithms has been used for chaos control: differential evolution, self-organizingmigrating algorithm, genetic algorithm, simulated annealing and evolutionary strategies in a total of 15 versions. For modeling of spatiotemporal chaos behavior, the so called coupled map lattices were used based on logistic equation to generate chaos. The main aim of this investigation was to show that evolutionary algorithms, under certain conditions, are capable of controlling of CML deterministic chaos, when the cost function is properly defined alongside the parameters of selected evolutionary algorithms. Investigation consists of four different case studies with increasing simulation complexity. For all algorithms each simulation was evaluated 100 times in order to show and check robustness of used methods. All data were processed and used in order to get summarized results and graphs.

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Author information

Authors and Affiliations

  1. Faculty of Applied Informatics, Tomas Bata University in Zlin, Nad Stranemi 4511, Zlin, 76001, Czech Republic

    Ivan Zelinka

  2. Faculty of Electrical Engineering and Computer Science, VSB-TUO, 17. listopadu 15, 708 33, Ostrava-Poruba, Czech Republic

    Ivan Zelinka

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  1. Ivan Zelinka
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Editor information

Editors and Affiliations

  1. Department of Applied Informatics Faculty of Applied Informatics, Tomas Bata Univerzity in Zlin, Nad Stranemi 4511, Zlin, 76001, Czech Republic

    Ivan Zelinka

  2. Department of Control Engineering Faculty of Electrical Engineering, Czech Technical University in Prague UTIA AV CR, Pod vodarenskou vezi 4, 182 08, Prague 8, Czech Republic

    Sergej Celikovsky

  3. Faculty of Electrical Engineering & Information Technology, HTWK Leipzig, 04251, Leipzig, Germany

    Hendrik Richter

  4. Department of Electronic Engineering, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon, Hong Kong SAR P. R. China

    Guanrong Chen

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Zelinka, I. (2010). Evolutionary Control of CML Systems. In: Zelinka, I., Celikovsky, S., Richter, H., Chen, G. (eds) Evolutionary Algorithms and Chaotic Systems. Studies in Computational Intelligence, vol 267. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10707-8_6

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  • DOI: https://doi.org/10.1007/978-3-642-10707-8_6

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-10706-1

  • Online ISBN: 978-3-642-10707-8

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