文献类型：期刊文献

英文题名：Data-Driven Output Containment Control of Heterogeneous Multiagent Systems: A Hierarchical Scheme

作者：Sader, Malika[1]; Li, Wenyu[2]; Yin, Yanhui[3]; Li, Zhongmei[4]; Huang, Dexian[5]; Liu, Zhongxin[2]; He, Xiao[5]; Shang, Chao[5]

机构：[1] Tsinghua University, Department of Automation, Beijing, 100084, China; [2] Nankai University, Coll. of Artif. Intell. Tianjin Key Lab. of Interventional Brain-Comp. Interface and Intelligent Rehab., Tianjin, 300350, China; [3] North-East Electric Power University, School of Automation Engineering, Jilin, 132000, China; [4] East China University of Science and Technology, Key Laboratory of Smart Manufacturing in Energy Chemical Process Ministry of Education, Shanghai, 200237, China; [5] Tsinghua University, Department of Automation Beijing National Research Center for Information Science and Technology, Beijing, 100084, China

年份：2024

起止页码：6889

外文期刊名：Proceedings of the IEEE Conference on Decision and Control

收录：EI(收录号：20251118040700)

语种：英文

摘要：In this article, we propose a data-driven solution to the output containment control problem of multiagent systems characterized by heterogeneous and unknown dynamics. The proposed data-driven scheme is hierarchical, which includes a network layer and a physical layer, bypassing the traditional modeling exercise and eliminating the need for explicit state-space models. In the network layer, a fully distributed observer without knowing the dynamics of leaders is designed to generate a containment trajectory. A data-driven approach based on data sampled from an auxiliary system is developed to overcome the dependence on the explicit state-space models for design of control gains. This paves the way for deriving a datadriven solution to the regulator equation, which is derived by employing the data informativity condition and relevant data in the physical layer. The results demonstrate that the closedloop system is asymptotically stable, and the regulated output containment converges to zero. Compared to generic modelbased hierarchical schemes, the assumptions that the system matrices are completely known and homogeneous on system dynamics can be relaxed. ? 2024 IEEE.