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Adaptive Backstepping Neural Network Control for Unknown Nonlinear Time-Delay 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

For a class of unknown nonlinear time-delay systems, an adaptive neural network (NN) control design is proposed in this paper. Bacsteppping, domination and adaptive bounding design technique are combined to construct an adaptive NN controller. Unknown time-delay functions are approximated by NNs. Based on the Lyapnov-Krasovikii functional, the sem-globally uniformly ultimately boundedness (SGUUB) of all the signals in the closed-loop systems is proved. The arbitrary output tracking accuracy is achieved by tuning the design parameters. The feasibility is investigated by an illustrative simulation example.

This work is supported by NSFC (60374015).

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Author information

Authors and Affiliations

  1. Department of Applied Mathematics, Xidian University, Xi’an, 710071, China

    Weisheng Chen & Junmin Li

Authors
  1. Weisheng Chen
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  2. Junmin Li
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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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Chen, W., Li, J. (2005). Adaptive Backstepping Neural Network Control for Unknown Nonlinear Time-Delay 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_5

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  • DOI: https://doi.org/10.1007/11427469_5

  • 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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