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An Adaptive Controller Using Wavelet Network for Five-Bar Manipulators with Deadzone Inputs

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Emerging Intelligent Computing Technology and Applications (ICIC 2013)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 375))

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Abstract

In this paper, an adaptive model-based control scheme is proposed for tracking control of five-bar manipulators with deadzone inputs. The proposed controller is based on the combination of nominal dynamic model of the five-bar manipulator, a wavelet network and a deadzone precompensator. The wavelet network and the precompensator are used for compensating the unknown deadzone inputs, modeling errors and uncertainties of the five-bar manipulator. The adaptation laws are derived for tuning parameters of the precompensator and wavelet network. The efficiency of the proposed control scheme is verified by comparative simulations.

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Author information

Authors and Affiliations

  1. Graduate School of Electrical Engineering, University of Ulsan, 680-749, Ulsan, South Korea

    Tien Dung Le

  2. School of Electrical Engineering, University of Ulsan, 680-749, Ulsan, South Korea

    Hee-Jun Kang

Authors
  1. Tien Dung Le
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  2. Hee-Jun Kang
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Editor information

Editors and Affiliations

  1. Machine Learning and Systems Biology Laboratory, School of Electronics and Information Engineering, Tongji University, Shanghai, China

    De-Shuang Huang

  2. Department of Computer Science and Engineering, Indian Institute of Technology Kanpur, 208 016, Kanpur, India

    Phalguni Gupta

  3. Tsinghua University, Beijing, China

    Ling Wang

  4. Department of Biotechnology, Indian Institute of Technology Madras, 600 036, Chennai, Tamilnadu, India

    Michael Gromiha

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© 2013 Springer-Verlag Berlin Heidelberg

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Le, T.D., Kang, HJ. (2013). An Adaptive Controller Using Wavelet Network for Five-Bar Manipulators with Deadzone Inputs. In: Huang, DS., Gupta, P., Wang, L., Gromiha, M. (eds) Emerging Intelligent Computing Technology and Applications. ICIC 2013. Communications in Computer and Information Science, vol 375. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39678-6_27

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  • DOI: https://doi.org/10.1007/978-3-642-39678-6_27

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-39677-9

  • Online ISBN: 978-3-642-39678-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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