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A Data-driven Intermediate Estimator-based Approach for Collaborative Fault-tolerant Tracking Control of Multi-agent Systems

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International Conference on Neural Computing for Advanced Applications (NCAA 2023)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1870))

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Abstract

This paper presents a data-driven distributed intermediate estimator-based cooperative tracking control method for multi-agent systems with actuator faults and unknown model parameters. A residual generator is constructed using the process input and output data of the system with unknown model parameters, and a new error state variable is constructed. Moreover, a distributed intermediate estimator is designed to estimate the combined unknown input signal of the followers. Based on this estimation signal, the control law is designed to compensate for the unknown inputs to the followers. Finally, the experimental results verify the effectiveness of the proposed method.

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Acknowledgement

   This work was supported in part by the Zhejiang Provincial Natural Science Foundation of China under Grant LZ21F030004, in part by the Key Research and Development Program of Zhejiang under Grant 2022C01018, and in part by the National Natural Science Foundation of China under Grant U21B2001.

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Authors and Affiliations

  1. Institute of Cyberspace Security, Zhejiang University of Technology, Hangzhou, 310023, China

    Lianghuan Ying, Junwei Zhu & Yasi Pan

Authors
  1. Lianghuan Ying
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  2. Junwei Zhu
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  3. Yasi Pan
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Corresponding author

Correspondence to Junwei Zhu .

Editor information

Editors and Affiliations

  1. Harbin Institute of Technology, Shenzhen, China

    Haijun Zhang

  2. Chaohu University, Hefei, China

    Yinggen Ke

  3. Chongqing University, Chongqing, China

    Zhou Wu

  4. South China Normal University, Guangzhou, China

    Tianyong Hao

  5. Hefei University of Technology, Hefei, China

    Zhao Zhang

  6. Technical University of Denmark, Kongens Lyngby, Denmark

    Weizhi Meng

  7. Chaohu University, Hefei, China

    Yuanyuan Mu

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Ying, L., Zhu, J., Pan, Y. (2023). A Data-driven Intermediate Estimator-based Approach for Collaborative Fault-tolerant Tracking Control of Multi-agent Systems. In: Zhang, H., et al. International Conference on Neural Computing for Advanced Applications. NCAA 2023. Communications in Computer and Information Science, vol 1870. Springer, Singapore. https://doi.org/10.1007/978-981-99-5847-4_38

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  • DOI: https://doi.org/10.1007/978-981-99-5847-4_38

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-99-5846-7

  • Online ISBN: 978-981-99-5847-4

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