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Adaptive Neural-Network Control for Redundant Nonholonomic Mobile Modular Manipulators

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Book cover 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 discusses the trajectory following issue for redundant nonholonomic mobile modular manipulators. Dynamic model is established and an adaptive neural-network controller is developed to control the end-effector to follow a desired spacial trajectory. The proposed algorithm doesn’t need any priori dynamics and provides a new solution for stabilization of redundant robotic self-motions. Simulation results for a real robot demonstrate the proposed algorithm is effective.

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References

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Author information

Authors and Affiliations

  1. Faculty of Science and Technology, University of Macau, Av. Padre Tomas Pereira S.J., Taipa, Macao S.A.R., P.R. China

    Yangmin Li & Yugang Liu

  2. Department of Precision Instruments and Mechanology, Tsinghua University, Beijing, 100084, P.R. China

    Shaoze Yan

Authors
  1. Yangmin Li
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  2. Yugang Liu
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  3. Shaoze Yan
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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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Li, Y., Liu, Y., Yan, S. (2005). Adaptive Neural-Network Control for Redundant Nonholonomic Mobile Modular Manipulators. 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_43

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  • DOI: https://doi.org/10.1007/11427469_43

  • 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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