Discernibility of topological variations for networked LTI systems based on observed output trajectories

Yuqing Hao*, Qingyun Wang, Zhisheng Duan, Guanrong Chen

*Corresponding author for this work

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

1 Citation (Scopus)

Abstract

In this paper, the possibility of detecting topological variations by observing output trajectories from networked linear time-invariant systems is investigated, where the network topology can be general, but the nodes have identical higher-dimensional dynamics. A necessary and sufficient condition on the discernibility of topological variations is derived, in terms of the eigenspaces of the original and the modified network configurations. By taking the specific network structures into consideration, some lower-dimensional conditions are derived, which reveal how the network topologies, sensor locations, node-system dynamics and output, as well as inner interactions altogether affect the discernibility. Furthermore, the output discernibility of topological changes for networked multi-agent systems is revisited, showing that some criterion reported in the literature does not hold. Consequently, a modified necessary and sufficient condition is established. The effectiveness of the results is demonstrated through several examples. © 2024 Elsevier Ltd
Original languageEnglish
Article number111547
JournalAutomatica
Volume163
Online published15 Feb 2024
DOIs
Publication statusPublished - May 2024

Funding

This work is supported by the National Natural Science Foundation of China under Grants 12172020 , 11932003 , T2121002 , in part by the Beijing Natural Science Foundation under Grant 1222010 , in part by the Young Elite Scientists Sponsorship Program by CAST under Grant 2022 QNRC001, and in part by the Hong Kong Research Grants Council under the GRF Grant CityU 11206320 .

Research Keywords

  • Discernibility
  • Networked systems
  • Output trajectory
  • Topological variation

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