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Nonlinear System Adaptive Control by Using Multiple Neural Network Models

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Advances in Neural Networks - ISNN 2006 (ISNN 2006)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3972))

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Abstract

Multiple radial based function (RBF)neural network models are used to cover the uncertainty of time variant nonlinear system, and multiple element controllers are set up based on the multiple RBF models. At every sample time, the closest model is selected by an index function which is formed by the integration of model output error. The element controller based on this model will be switched as the controller of the controlled system. This kind of multiple model adaptive controller (MMAC)is an extension of the MMAC in linear system, and it can improve the transient response and performance of the controlled system greatly.

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Author information

Authors and Affiliations

  1. Department of Automation, Information and Engineering School, University of Science and Technology Beijing, Beijing, 100083, P.R.China

    Xiao-Li Li & Yun-Feng Kang

  2. Research Center of Information and Control, Dalian University of Technology, Dalian, 116024, P.R. China

    Wei Wang

Authors
  1. Xiao-Li Li
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  2. Yun-Feng Kang
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  3. Wei Wang
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Editor information

Editors and Affiliations

  1. Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China

    Jun Wang

  2. Computational Intelligence Laboratory, School of Computer Science and Engineering, University of Electronic Science and Technology of China, 610054, Chengdu, P.R. China

    Zhang Yi

  3. Department of Electrical Engineering, University of Louisville, 40292, Louisville, KY, U.S.A

    Jacek M. Zurada

  4. Laboratory for Computational Biology, Shanghai Center for Systems Biomedicine, 800 Dong Chuan Rd., 200240, Shanghai, China

    Bao-Liang Lu

  5. School of Electrical and Electronic Engineering, University of Manchester, UK

    Hujun Yin

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© 2006 Springer-Verlag Berlin Heidelberg

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Li, XL., Kang, YF., Wang, W. (2006). Nonlinear System Adaptive Control by Using Multiple Neural Network Models. In: Wang, J., Yi, Z., Zurada, J.M., Lu, BL., Yin, H. (eds) Advances in Neural Networks - ISNN 2006. ISNN 2006. Lecture Notes in Computer Science, vol 3972. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11760023_128

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  • DOI: https://doi.org/10.1007/11760023_128

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-34437-7

  • Online ISBN: 978-3-540-34438-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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