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Neural Networks Robust Adaptive Control for a Class of MIMO Uncertain Nonlinear Systems

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Advances in Neural Networks – ISNN 2005 (ISNN 2005)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3498))

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Abstract

This paper presents a robust adaptive control scheme for a class of multi-input multi-output (MIMO) uncertain nonlinear systems. Multiple multi-layer neural networks are used to compensate for the model uncertainty. The on-line updating rules of the neural networks parameters are obtained by Lyapunov stability theory. All signals in the closed-loop system are bounded. The output tracking error converges to a small neighborhood of zero, while the stability of the closed-loop system is guaranteed. Finally the effectiveness of the control scheme is verified by a simulation of two-link manipulator.

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Author information

Authors and Affiliations

  1. State Key Lab of Intelligent Technology and Systems, Department of Computer Science and Technology, Tsinghua University, Beijing, 100084, China

    Tingliang Hu, Jihong Zhu, Chunhua Hu & Zengqi Sun

Authors
  1. Tingliang Hu
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  2. Jihong Zhu
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  3. Chunhua Hu
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  4. Zengqi Sun
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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. The Key Laboratory of Optoelectric Technology & Systems, Ministry of Education, China

    Xiao-Feng Liao

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

    Zhang Yi

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© 2005 Springer-Verlag Berlin Heidelberg

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Hu, T., Zhu, J., Hu, C., Sun, Z. (2005). Neural Networks Robust Adaptive Control for a Class of MIMO Uncertain Nonlinear Systems. In: Wang, J., Liao, XF., Yi, Z. (eds) Advances in Neural Networks – ISNN 2005. ISNN 2005. Lecture Notes in Computer Science, vol 3498. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11427469_10

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  • DOI: https://doi.org/10.1007/11427469_10

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-25914-5

  • Online ISBN: 978-3-540-32069-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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