In this paper, intelligent devices in industrial manufacturing are modeled as the nodes in the network systems. The sampled-data control is adopted to guarantee the synchronization of the network systems. The proposed sampled-data control strategy can reduce the updating frequency of the controller and the network communication burden. The closed-loop system is equivalently rewritten as the feedback interaction of a linear time-invariant system and a time-delay operator. The small gain theorem is utilized to calculate the upper bound of the sampling intervals. Furthermore, the integral quadratic constraints can provide the passivity-type property of the operator and give less-conservative results. Moreover, in order to further use the information about the sampling pattern and sawtooth structure, the time-delay integral operator is replaced by sample-data integral operator, and less-conservative results are proposed. Finally, the effectiveness of the proposed sampled-data distributed control strategy is demonstrated by a numerical example.

中文翻译：

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工业制造中网络系统的采样数据控制

在本文中，工业制造中的智能设备被建模为网络系统中的节点。采用采样数据控制，保证网络系统同步。所提出的采样数据控制策略可以减少控制器的更新频率和网络通信负担。闭环系统等效地改写为线性时不变系统和时滞算子的反馈相互作用。小增益定理用于计算采样间隔的上限。此外，积分二次约束可以提供算子的被动类型属性，并给出不太保守的结果。此外，为了进一步利用采样模式和锯齿结构的信息，将时滞积分算子替换为样本数据积分算子，提出了不太保守的结果。最后，通过数值例子证明了所提出的采样数据分布式控制策略的有效性。