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Parameter identification of Rossler’s chaotic system by an evolutionary algorithm

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  • Chang, Wei-Der

Abstract

In this paper, a differential evolution (DE) algorithm is applied to parameter identification of Rossler’s chaotic system. The differential evolution has been shown to possess a powerful searching capability for finding the solutions for a given optimization problem, and it allows for parameter solution to appear directly in the form of floating point without further numerical coding or decoding. Three unknown parameters of Rossler’s Chaotic system are optimally estimated by using the DE algorithm. Finally, a numerical example is given to verify the effectiveness of the proposed method.

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  • Chang, Wei-Der, 2006. "Parameter identification of Rossler’s chaotic system by an evolutionary algorithm," Chaos, Solitons & Fractals, Elsevier, vol. 29(5), pages 1047-1053.
    • Handle: RePEc:eee:chsofr:v:29:y:2006:i:5:p:1047-1053
    DOI: 10.1016/j.chaos.2005.08.121
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    3. Berczyñski, Stefan & Kravtsov, Yury A. & Anosov, Oleg, 2009. "Chaotic dynamics reconstruction from noisy data: Phenomenon of predictability worsening for incomplete set of observables," Chaos, Solitons & Fractals, Elsevier, vol. 41(3), pages 1459-1466.
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