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Switching Set-Point Control of Nonlinear System Based on RBF Neural Network

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Advances in Neural Networks – ISNN 2007 (ISNN 2007)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4491))

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Abstract

Multiple controllers based on multiple radial based function neural network(RBFNN) models are used to control a nonlinear system to trace a set-point. Considering the nonlinearity of the system, when the set-point value is time variant, a controller based on a fixed structure RBFNN can not give a good control performance. A switching controller which switches among different controller based on different RBFNN is used to adapt the varing set-point value and improve the output reponse and control performance of the nonlinear system.

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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, China

    Xiao-Li Li

Authors
  1. Xiao-Li Li
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Editor information

Editors and Affiliations

  1. Department of Electrical and Computer Engineering (M/C 154), University of Illinois at Chicago, 851 S. Morgan Street, 60607-7053, Chicago, IL, USA

    Derong Liu

  2. School of Automation, Southeast University, 210096, Nanjing, China

    Shumin Fei

  3. Laboratory of Complex Systems, Institute of Automation, Chinese Adacemy of Sciences, 100080, Beijing, P. R. China

    Zeng-Guang Hou

  4. School of Information Science and Engineering, Northeast University, Shenyang, 110004, China

    Huaguang Zhang

  5. School of Electrical Engineering, Hohai University, Nanjing, 210098, China

    Changyin Sun

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© 2007 Springer-Verlag Berlin Heidelberg

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Li, XL. (2007). Switching Set-Point Control of Nonlinear System Based on RBF Neural Network. In: Liu, D., Fei, S., Hou, ZG., Zhang, H., Sun, C. (eds) Advances in Neural Networks – ISNN 2007. ISNN 2007. Lecture Notes in Computer Science, vol 4491. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72383-7_12

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  • DOI: https://doi.org/10.1007/978-3-540-72383-7_12

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-72382-0

  • Online ISBN: 978-3-540-72383-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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