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Linear Time-Varying Model Predictive Control for Trajectory-Tracking of a Wheeled Mobile Robot

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Neural Computing for Advanced Applications (NCAA 2021)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1449))

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Abstract

In this paper, a linear time-varying model predictive control (MPC) is proposed for the wheeled mobile robot to track the reference trajectory. The nonlinear model subject to the non-holonomic constraint is linearized and discretized into a linear time-varying model, such that the time-varying MPC can be applied. The MPC algorithm is processed with the linear time-varying model. Recursive feasibility and closed-loop stability are proved in the framework of time-varying systems, while the control inputs (linear and angular velocities) are proved to be bounded within their constraints. A simulation example is provided to support the theoretical result.

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Acknowledgement

This work was supported by National Natural Science Foundation of China under grants 62073015 and 61703018.

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Authors and Affiliations

  1. The Seventh Research Division, Beihang University, Beijing, 100191, People’s Republic of China

    Juntao Wei & Bing Zhu

Authors
  1. Juntao Wei
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  2. Bing Zhu
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Corresponding author

Correspondence to Bing Zhu .

Editor information

Editors and Affiliations

  1. Harbin Institute of Technology, Shenzhen, China

    Haijun Zhang

  2. Nanfang College of Sun Yat-sen University, Guangzhou, China

    Zhi Yang

  3. Hefei University of Technology, Hefei, China

    Zhao Zhang

  4. Chongqing University, Chongqing, China

    Zhou Wu

  5. South China Normal University, Guangzhou, China

    Tianyong Hao

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Wei, J., Zhu, B. (2021). Linear Time-Varying Model Predictive Control for Trajectory-Tracking of a Wheeled Mobile Robot. In: Zhang, H., Yang, Z., Zhang, Z., Wu, Z., Hao, T. (eds) Neural Computing for Advanced Applications. NCAA 2021. Communications in Computer and Information Science, vol 1449. Springer, Singapore. https://doi.org/10.1007/978-981-16-5188-5_38

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  • DOI: https://doi.org/10.1007/978-981-16-5188-5_38

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-16-5187-8

  • Online ISBN: 978-981-16-5188-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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