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Adaptive Fast Finite-Time Consensus for Second-Order Multi-agent Systems

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Proceedings of the 11th International Conference on Modelling, Identification and Control (ICMIC2019)

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 582))

Abstract

We will study  the adaptive fast finite-time consensus (FTC) control problem  of second-order multi-agent systems (MASs) with  unknown dynamics and external disturbances in this paper. Based on the basis of radial basis function neural networks theories, we use it to approximate the unknown functions. According to the consensus protocols and adaptive laws, we will prove that velocity errors of arbitrary two agents reach a small region of zero in finite time as well as position errors. Ultimately, the effectiveness of the designed method is tested through a numerical example.

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Acknowledgements

This work is supported by the National Natural Science Foundation (NNSF) of China (61803215), the Natural Science Foundation of Shandong Province (ZR2019BF038), and Qingdao Application Basic Research Project (18-2-2-40-jch).

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Authors and Affiliations

  1. School of Automation, Qingdao University, Qingdao, 266071, People’s Republic of China

    Jiabo Ren, Baofang Wang & Mingjie Cai

Authors
  1. Jiabo Ren
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  2. Baofang Wang
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  3. Mingjie Cai
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Corresponding author

Correspondence to Mingjie Cai .

Editor information

Editors and Affiliations

  1. College of Electronic Information and Automation, Civil Aviation University of China, Tianjin, China

    Rui Wang

  2. Department of Automation, Nankai University, Tianjin, China

    Zengqiang Chen

  3. Department of Automation, University of Science and Technology Beijing, Beijing, China

    Weicun Zhang

  4. Department of Engineering Design and Mathematics, University of the West of England, Bristol, UK

    Quanmin Zhu

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Ren, J., Wang, B., Cai, M. (2020). Adaptive Fast Finite-Time Consensus for Second-Order Multi-agent Systems. In: Wang, R., Chen, Z., Zhang, W., Zhu, Q. (eds) Proceedings of the 11th International Conference on Modelling, Identification and Control (ICMIC2019). Lecture Notes in Electrical Engineering, vol 582. Springer, Singapore. https://doi.org/10.1007/978-981-15-0474-7_100

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