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Data-driven consensus control of fully distributed event-triggered multi-agent systems

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Abstract

This study investigates the consensus control issue in discrete-time linear multi-agent systems (MASs) using data-driven control under undirected communication networks. To alleviate the communication burden, an adaptive event-triggered control strategy involving only local information is proposed and a model-based stability condition is derived that guarantees the asymptotic consensus of MASs. Furthermore, a data-based consensus condition for unknown MASs is established by combining a data-based system representation with the model-based stability condition, using only pre-collected noisy input-state data instead of the accurate system information a priori. Specifically, both model-based and data-driven event-triggered controllers can be utilized without requiring any global information. The validity and correctness of the controllers and associated theoretical results are demonstrated via numerical simulations.

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Acknowledgements

The work was supported in part by National Key R&D Program of China (Grant No. 2021YFB1714800), National Natural Science Foundation of China (Grant Nos. 62173034, 61925303, 62088101), and Natural Science Foundation of Chongqing (Grant No. 2021ZX4100027).

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Correspondence to Gang Wang.

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Li, Y., Wang, X., Sun, J. et al. Data-driven consensus control of fully distributed event-triggered multi-agent systems. Sci. China Inf. Sci. 66, 152202 (2023). https://doi.org/10.1007/s11432-022-3629-1

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  • DOI: https://doi.org/10.1007/s11432-022-3629-1

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