Discernibility of Topological Variations for Networked LTI Systems

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

6 Scopus Citations
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Detail(s)

Original languageEnglish
Pages (from-to)377-384
Journal / PublicationIEEE Transactions on Automatic Control
Volume68
Issue number1
Online published23 Dec 2021
Publication statusPublished - Jan 2023

Abstract

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 (Patil et al., 2019) and (Roy et al., 2020), 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 (Roy et al., 2020), 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

Citation Format(s)

Discernibility of Topological Variations for Networked LTI Systems. / Hao, Yuqing; Wang, Qingyun; Duan, Zhisheng et al.
In: IEEE Transactions on Automatic Control, Vol. 68, No. 1, 01.2023, p. 377-384.

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review