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Fuzzy Sliding Mode Trajectory Tracking Control for Omnidirectional Mobile Robots Based on Exponential Convergence Law

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6GN for Future Wireless Networks (6GN 2023)

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Abstract

The increasing advancements in information technology have led to a growing interest in control research for mobile robot trajectory tracking. A controller for robot systems should exhibit adaptivity and robustness as its fundamental characteristics. Sliding mode control (SMC) offers strong robustness but is hindered by the presence of chattering, limiting its application and development. This paper explores the integration of sliding mode control and fuzzy control to address these limitations. By using the mobile robot’s kinematic model, a sliding mode controller based on exponential convergence is designed on the basis of existing sliding mode controllers, incorporating a fuzzy algorithm to mitigate system chattering. Experimental results demonstrate a significant improvement in control performance compared to traditional SMC, with faster convergence of tracking error and enhanced robustness.

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Authors and Affiliations

  1. Shanghai Dianji University, Shanghai, 201306, China

    Ding Ruiao, Ji Chunlei & Zeng Xiangxu

Authors
  1. Ding Ruiao
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  2. Ji Chunlei
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  3. Zeng Xiangxu
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Corresponding author

Correspondence to Ji Chunlei .

Editor information

Editors and Affiliations

  1. Shanghai Dianji University, Shanghai, China

    Jingchao Li

  2. Kanagawa University, Yokohama, Japan

    Bin Zhang

  3. Shanghai University of Electric Power, Yangpu, China

    Yulong Ying

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© 2024 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Ruiao, D., Chunlei, J., Xiangxu, Z. (2024). Fuzzy Sliding Mode Trajectory Tracking Control for Omnidirectional Mobile Robots Based on Exponential Convergence Law. In: Li, J., Zhang, B., Ying, Y. (eds) 6GN for Future Wireless Networks. 6GN 2023. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 554. Springer, Cham. https://doi.org/10.1007/978-3-031-53404-1_18

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  • DOI: https://doi.org/10.1007/978-3-031-53404-1_18

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-53403-4

  • Online ISBN: 978-3-031-53404-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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