A Necessary Condition for Network Identifiability With Partial Excitation and Measurement

• 成果类型: Article
• 署名作者: Cheng, Xiaodong; Shi, Shengling; Lestas, Ioannis; Van den Hof, Paul M. J.
• 署名单位: University of Cambridge; Wageningen University & Research; Eindhoven University of Technology
• 刊物名称: IEEE TRANSACTIONS ON AUTOMATIC CONTROL
• ISSN/ISSBN: 0018-9286
• DOI: 10.1109/TAC.2023.3239829
• 发表日期: 2023
• 页码: 6820-6827
• 关键词: Bipartite graph; data-driven modeling; Directed graphs; graph theory; Network systems; system identification.

摘要

This article considers dynamic networks where vertices and edges represent manifest signals and causal dependencies among the signals, respectively. We address the problem of how to determine if the dynamics of a network can be identified when only partial vertices are measured and excited. A necessary condition for network identifiability is presented, where the analysis is performed based on identifying the dependency of a set of rational functions from excited vertices to measured ones. This condition is further characterized by using an edge-removal procedure on the associated bipartite graph. Moreover, on the basis of necessity analysis, we provide a necessary and sufficient condition for identifiability in circular networks.