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International Symposium on Neural Networks

ISNN 2017: Advances in Neural Networks - ISNN 2017 pp 109–117Cite as

Neuro Adaptive Control of Asymmetrically Driven Mobile Robots with Uncertainties

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10262))

Abstract

This paper presents an adaptive tracking control scheme for asymmetrically actuated wheeled mobile robot (WMR) with uncertain/unknown mass center. First, we establish the WMR dynamic model with consideration of the fact that its center of mass is normally unknown or even shifting due to dynamic loading and/or load shifting. Second, a structurally simple controller is developed to deal with time-varying unknown control gain and parametric/non-parametric uncertainties of WMR, where the asymmetric and non-smooth input saturation with no a prior knowledge of bounds of input saturation is addressed.

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References

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Acknowledgments

This work is supported in part by technology transformation program of Chongqing higher education university (KJZH17102), the National Natural Science Foundation of China (No. 51374264), and the China Scholarship Council (No. 201508505045).

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Authors and Affiliations

  1. Key Laboratory of Dependable Service Computing in Cyber Physical Society of Ministry of Education, Chongqing University, Chongqing, 400044, China

    Zhixi Shen, Yaping Ma & Yongduan Song

Authors
  1. Zhixi Shen
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  2. Yaping Ma
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  3. Yongduan Song
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Corresponding author

Correspondence to Yongduan Song .

Editor information

Editors and Affiliations

  1. Dalian University of Technology, Dalian, China

    Fengyu Cong

  2. City University of Hong Kong, Kowloon Tong, Hong Kong

    Andrew Leung

  3. Chinese Academy of Sciences, Beijing, China

    Qinglai Wei

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Shen, Z., Ma, Y., Song, Y. (2017). Neuro Adaptive Control of Asymmetrically Driven Mobile Robots with Uncertainties. In: Cong, F., Leung, A., Wei, Q. (eds) Advances in Neural Networks - ISNN 2017. ISNN 2017. Lecture Notes in Computer Science(), vol 10262. Springer, Cham. https://doi.org/10.1007/978-3-319-59081-3_14

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  • DOI: https://doi.org/10.1007/978-3-319-59081-3_14

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-59080-6

  • Online ISBN: 978-3-319-59081-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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