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Volume 10 Issue 2
Feb.  2023

IEEE/CAA Journal of Automatica Sinica

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X. Wang, J. Sun, G. Wang, F. Allgöwer, and J. Chen, “Data-driven control of distributed event-triggered network systems,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 2, pp. 351–364, Feb. 2023. doi: 10.1109/JAS.2023.123225
Citation: X. Wang, J. Sun, G. Wang, F. Allgöwer, and J. Chen, “Data-driven control of distributed event-triggered network systems,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 2, pp. 351–364, Feb. 2023. doi: 10.1109/JAS.2023.123225

Data-Driven Control of Distributed Event-Triggered Network Systems

doi: 10.1109/JAS.2023.123225
Funds:  This work was supported in part by the National Key Research and Development Program of China (2021YFB1714800), the National Natural Science Foundation of China (62088101, 61925303, 62173034, U20B2073), the Natural Science Foundation of Chongqing (2021ZX4100027), and the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germanys Excellence Strategy— EXC 2075-390740016 (468094890)
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  • The present paper deals with data-driven event-triggered control of a class of unknown discrete-time interconnected systems (a.k.a. network systems). To this end, we start by putting forth a novel distributed event-triggering transmission strategy based on periodic sampling, under which a model-based stability criterion for the closed-loop network system is derived, by leveraging a discrete-time looped-functional approach. Marrying the model-based criterion with a data-driven system representation recently developed in the literature, a purely data-driven stability criterion expressed in the form of linear matrix inequalities (LMIs) is established. Meanwhile, the data-driven stability criterion suggests a means for co-designing the event-triggering coefficient matrix and the feedback control gain matrix using only some offline collected state-input data. Finally, numerical results corroborate the efficacy of the proposed distributed data-driven event-triggerednetwork system (ETS) in cutting off data transmissions and the co-design procedure.

     

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    Highlights

    • A data-driven event-triggered control of a class of unknown discrete-time interconnected systems (a.k.a. network systems) using purely input-state data
    • A novel dynamic distributed event-triggered transmission scheme only involving the discrete-time state information of each subsystem and its neighbor(s) at sampling instants
    • Model-based and data-driven methods for co-designing the controller and the event-triggering matrices, based on discrete-time looped-functional approach

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