Discernibility of Topological Variations for Networked LTI Systems

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

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Original languageEnglish
Journal / PublicationIEEE Transactions on Automatic Control
Online published23 Dec 2021
Publication statusOnline published - 23 Dec 2021


In this paper, the discernibility of topological variations for networked linear time-invariant (LTI) systems is investigated, where the network topology is general, and the nodes have identical higher-dimensional dynamics. A necessary and sufficient condition on the discernibility is derived, revealing how the topological variations, node-system dynamics and inner interactions altogether affect the discernibility of the network. Compared with the existing conditions in [28] and [31], which require the network topology to be undirected, this condition is more general. Furthermore, the discernibility of topological variations for multi-agent systems is revisited. A new necessary and sufficient condition is established, and the indiscernible space is completely characterized. Differing from the condition provided in [31], this condition removes the requirements on the multi-agent system and has broader applicability. The effectiveness of the results is demonstrated by several examples.

Research Area(s)

  • Artificial neural networks, Brain modeling, discernibility, Eigenvalues and eigenfunctions, indiscernible state, Linear systems, Multi-agent systems, Network topology, Networked systems, topological variation, Topology