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Robust Adaptive Fuzzy Control for Uncertain Nonlinear Systems

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Fuzzy Systems and Knowledge Discovery (FSKD 2005)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3613))

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Abstract

Two different fuzzy control approaches are proposed for a class of nonlinear systems with mismatched uncertainties, transformable to the strict-feedback form. A fuzzy logic system (FLS) is used as a universal approximator to approximate unstructured uncertain functions and the bounds of the reconstruction errors are estimated online. By employing special design techniques, the controller singularity problem is completely avoided for the two approaches. Furthermore, all the signals in the closed-loop systems are guaranteed to be semi-globally uniformly ultimately bounded and the outputs of the system are proved to converge to a small neighborhood of the desired trajectory. The control performance can be guaranteed by an appropriate choice of the design parameters. In addition, the proposed fuzzy controllers are highly structural and particularly suitable for parallel processing in the practical applications.

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Author information

Authors and Affiliations

  1. National Key Laboratory of Industrial Control Technology, Institute of Advanced Process Control, Zhejiang University, Hangzhou, 310027, P. R. China

    Chen Gang, Shuqing Wang & Jianming Zhang

Authors
  1. Chen Gang
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  2. Shuqing Wang
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  3. Jianming Zhang
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Editor information

Editors and Affiliations

  1. School of Electrical and Electronic Engineering, Nanyang Technological University, Block S1, Nanyang Avenue, 639798, Singapore

    Lipo Wang

  2. Honda Research Institute Europe GmbH, Offenbach/Main, Germany

    Yaochu Jin

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© 2005 Springer-Verlag Berlin Heidelberg

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Gang, C., Wang, S., Zhang, J. (2005). Robust Adaptive Fuzzy Control for Uncertain Nonlinear Systems. In: Wang, L., Jin, Y. (eds) Fuzzy Systems and Knowledge Discovery. FSKD 2005. Lecture Notes in Computer Science(), vol 3613. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11539506_104

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  • DOI: https://doi.org/10.1007/11539506_104

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-28312-6

  • Online ISBN: 978-3-540-31830-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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