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Character Istics Recognition of Typical Fractional Order Dynamical Systems via Orthogonal Wavelet Packet Analysis Method

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Advances in Computer Science, Intelligent System and Environment

Part of the book series: Advances in Intelligent and Soft Computing ((AINSC,volume 104))

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Abstract

The orthogonal wavelet packet analysis is a method applied on dynamics recognition of fractional order system. Firstly, the signals band was split up into proper levels and the sub signals were gained, which correspond to each frequency band according to the average period of the time series. Then by analysis of sub frequency band power distribution in the signals total power, the chaos in the related signal can be easily identifed. Finally, by taking the controlled fractional order chen’s system as an illustration, the results obtained by this procedure agree with power spectrum method. So this new method can be used for dynamics recognition in fractional order systems.

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Author information

Authors and Affiliations

  1. Network Management Center, Xinxiang University, Henan, Xinxiang, China, 453003

    Tao Zhang

  2. Network Center, Henan Institute of Science and Technology, Xinxiang, China, 453003

    Wenxian Xiao & Zhen Liu

  3. Foreign Language Department, Henan Institute of Science and Technology, Henan, Xinxiang, China, 453003

    Wenlong Wan

Authors
  1. Tao Zhang
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  2. Wenxian Xiao
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  3. Zhen Liu
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  4. Wenlong Wan
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Editor information

Editors and Affiliations

  1. Wuhan Section, International Science & Education Researcher Association, Special No.1 Jiangxia Road of Wuhan, Wuhan, China

    David Jin

  2. Guangzhou Section, International Science & Education Researcher Association, No.144, Jinheng Road Jinbi Garden 85-1102 southern Road of Industry Avenue Haizhu District, Guangzhou, Guang Dong provience, China

    Sally Lin

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Zhang, T., Xiao, W., Liu, Z., Wan, W. (2011). Character Istics Recognition of Typical Fractional Order Dynamical Systems via Orthogonal Wavelet Packet Analysis Method. In: Jin, D., Lin, S. (eds) Advances in Computer Science, Intelligent System and Environment. Advances in Intelligent and Soft Computing, vol 104. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23777-5_102

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  • DOI: https://doi.org/10.1007/978-3-642-23777-5_102

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-23776-8

  • Online ISBN: 978-3-642-23777-5

  • eBook Packages: EngineeringEngineering (R0)

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