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Fuzzy adaptive finite-time consensus tracking control for nonlinear multi-agent systems

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  • Lili Zhang
  • Bing Chen
  • Chong Lin
  • Yun Shang

Abstract

This paper focuses on the finite-time consensus tracking control problem of nonlinear multi-agent systems. Dynamics of each agent has completely unknown nonlinear terms that cannot be directly used for control design. Therefore, fuzzy logic systems are employed to approximate these nonlinear functions. Furthermore, a finite-time fuzzy adaptive consensus tracking protocol is proposed for a class of nonlinear multi-agent systems by using integral-type Lyapunov functions. The developed adaptive backstepping design scheme successfully avoids the singularity problem of the derivatives of virtual control signals. It is shown that with the presented control protocol, the consensus tracking errors converge to a small neighbourhood of the origin in finite time, and the other signals of multi-agent systems are bounded. Finally, a numerical example is used to verify the effectiveness of the proposed control protocol.

Suggested Citation

  • Lili Zhang & Bing Chen & Chong Lin & Yun Shang, 2021. "Fuzzy adaptive finite-time consensus tracking control for nonlinear multi-agent systems," International Journal of Systems Science, Taylor & Francis Journals, vol. 52(7), pages 1346-1358, May.
    • Handle: RePEc:taf:tsysxx:v:52:y:2021:i:7:p:1346-1358
    DOI: 10.1080/00207721.2020.1856450
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    Cited by:

    1. Wenqiang Wu & Jiarui Liu & Fangyi Li & Yuanqing Zhang & Zikai Hu, 2023. "Prescribed Settling Time Adaptive Neural Network Consensus Control of Multiagent Systems with Unknown Time-Varying Input Dead-Zone," Mathematics, MDPI, vol. 11(4), pages 1-21, February.

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