基于数据的网络系统同步方法
Data-driven Synchronization for Network Systems with Noiseless Data
AI总结：
本文提出了一种基于数据的网络系统同步方法，通过收集单个系统的输入-状态数据并结合网络拓扑，提供判断同步性的必要和充分条件，并通过数值模拟验证了方法的有效性。
摘要：
对于由协议相互连接的一组同构线性时不变系统，给定网络拓扑和系统模型，可以获取反馈增益以实现网络同步。然而，当系统模型未知时，基于模型的方法无法应用。因此，本文研究了同构网络的基于数据的同步问题。具体而言，给定一组LTI系统，从单个系统中收集输入-状态数据。然后，给定网络拓扑，提供基于数据的必要和充分条件以判断同步性。一旦条件满足，还可以直接从数据中获得反馈增益以同步网络，所采用的设计方法在本文中提供。最后，我们通过数值模拟来说明我们的结果。
英文摘要：
For a collection of homogeneous LTI systems that is interconnected by a protocol, given the network topology and the system model, one may obtain a feedback gain to synchronize the network. However, the model-based methods cannot be applied in case the system model is unknown. Therefore, in this paper, we study the data-driven synchronization problem for homogeneous networks. In particular, given a collection of LTI systems, we collect the input-state data from one individual system. Then, given the network topology, we provide data-based necessary and sufficient conditions for synchronizability. Once the conditions are satisfied, one can also obtain a feedback gain directly from data to synchronize the network with the corresponding design method provided in this paper. Finally, we illustrate our results with a numerical simulation.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
