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GFHM Model and Control for Uncertain Chaotic System

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Computational Intelligence (ICIC 2006)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4114))

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Abstract

This paper develops a fuzzy hyperbolic control method for chaotic continuous-time systems with uncertainties. First, the generalized fuzzy hyperbolic model (GFHM) is used to model unknown part of a chaotic system. Second, based on Lyapunov functional approach, a sufficient condition for a fuzzy hyperbolic controller and a state feedback controller is given such that the closed-loop system is asymptotic stable. Moreover, considering the influence of both approximation error and external disturbance, fuzzy hyperbolic H ā€‰āˆžā€‰ control scheme is addressed . All the results are given in terms of LMI forms, the effectiveness of the proposed method is shown by a simulation example.

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Authors and Affiliations

  1. School of Information Science and Engineering, Northeastern University, Shenyang, Liaoning 110004, China

    Dongsheng Yang, Huaguang Zhang, Zhiliang Wang & Yingchun Wang

Authors
  1. Dongsheng Yang
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  2. Huaguang Zhang
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  3. Zhiliang Wang
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  4. Yingchun Wang
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Editor information

Editors and Affiliations

  1. Institute of Intelligent Machines , Chinese Academy of Sciences , Anhui, Hefei, China

    De-Shuang Huang

  2. Queenā€™s University , Belfast, UK

    Kang Li  & George William Irwin  & 

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Ā© 2006 Springer-Verlag Berlin Heidelberg

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Yang, D., Zhang, H., Wang, Z., Wang, Y. (2006). GFHM Model and Control for Uncertain Chaotic System. In: Huang, DS., Li, K., Irwin, G.W. (eds) Computational Intelligence. ICIC 2006. Lecture Notes in Computer Science(), vol 4114. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-37275-2_6

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  • DOI: https://doi.org/10.1007/978-3-540-37275-2_6

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-37274-5

  • Online ISBN: 978-3-540-37275-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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