Stability margin of undirected homogeneous relative sensing networks: A geometric perspective

Research output: Contribution to journalArticlepeer-review

Abstract

In this paper, we study the stability margin (SM) of undirected homogeneous relative sensing networks (UH-RSNs) from a geometric point of view. SM is an important robustness measure indicating the amount of simultaneous gain and phase perturbations in the feedback channels before the instability occurs. A UH-RSN is characterized by the identical local dynamics (a single-input-single-output (SISO) open-loop transfer function Tloc(s)) of individual agent and the graph Laplacian LG representing how the agents are connected. It is shown in this paper that UH-RSNs having multiple inputs and outputs in general may be represented as a unity feedback system including the SISO Tloc(s) and one of the real eigenvalues of LG. This representation then helps to identify a class of cooperative Tloc(s) for which (1) SM becomes maximized or equal to 1 when the network's connectivity (the second smallest eigenvalue of LG) is greater than or equal to the curvature of the Nyquist plot of Tloc(s) at the origin; and (2) two bounds on SM are obtained for the SM estimation based on the geometric shape of Nyquist plot. Also, the representation of unity feedback system implies that UH-RSNs with non-cooperative Tloc(s) become unstable when the agents are joined with high connectivity. Numerical examples are provided to demonstrate these findings.

Original languageEnglish
Article number105027
JournalSystems and Control Letters
Volume156
DOIs
Publication statusPublished - 1 Oct 2021
Externally publishedYes

Keywords

  • Curvature
  • Laplacian matrix
  • Nyquist plot
  • Relative sensing network
  • Stability margin

Fingerprint

Dive into the research topics of 'Stability margin of undirected homogeneous relative sensing networks: A geometric perspective'. Together they form a unique fingerprint.

Cite this