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Neural-network-based fully distributed formation control for nonlinear multi-agent systems with event-triggered communication

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Abstract

This paper investigates the consensus-based formation control problem for multi-agent systems with unknown nonlinear dynamics. To achieve the desired formation, we propose two formation controllers to achieve the desired formation, one based on system states and the other on system outputs. The proposed controllers utilize adaptive gains to avoid global information and neural networks to estimate and compensate for nonlinearities. The proposed event-triggered schemes avoid continuous communication among agents and exclude the Zeno behavior. Stability analysis reveals that formation errors are bounded, and numerical simulations are used to validate the effectiveness of the proposed approaches.

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Authors and Affiliations

  1. School of Automation Science and Electrical Engineering, Beihang University, Beijing, 100191, China

    GuoLiang Zhu, KeXin Liu, HaiBo Gu & JinHu Lü

  2. Zhongguancun Laboratory, Beijing, 100094, China

    KeXin Liu, HaiBo Gu & JinHu Lü

Authors
  1. GuoLiang Zhu
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  2. KeXin Liu
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  3. HaiBo Gu
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  4. JinHu Lü
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Corresponding author

Correspondence to JinHu Lü.

Additional information

This work was supported by the National Key R&D Program of China (Grant No. 2022YFB3305600), the National Natural Science Foundation of China (Grant Nos. 62103015, 62141604 and 92067204), and the Fundamental Research Funds for Central Universities of China (Grant No. YWF-23-03-QB-019).

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Zhu, G., Liu, K., Gu, H. et al. Neural-network-based fully distributed formation control for nonlinear multi-agent systems with event-triggered communication. Sci. China Technol. Sci. 67, 209–220 (2024). https://doi.org/10.1007/s11431-022-2410-1

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  • DOI: https://doi.org/10.1007/s11431-022-2410-1

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