Relationship Between the Number of Agents and Sparse Observability Index

The state estimation problem in the presence of malicious sensor attacks is commonly referred to as a secure state estimation problem. Central to addressing this problem is the concept of the sparse observability index, defined as the largest integer <inline-formula><tex-math notation="...

Full description

Saved in:
Bibliographic Details
Main Authors: T. Shinohara, T. Namerikawa
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Open Journal of Control Systems
Subjects:
Online Access:https://ieeexplore.ieee.org/document/10989748/
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:The state estimation problem in the presence of malicious sensor attacks is commonly referred to as a secure state estimation problem. Central to addressing this problem is the concept of the sparse observability index, defined as the largest integer <inline-formula><tex-math notation="LaTeX">$ \delta$</tex-math></inline-formula> for which the system remains observable after the removal of any <inline-formula><tex-math notation="LaTeX">$\delta$</tex-math></inline-formula> sensors. This index plays a critical role in quantifying the resilience of the system, as a higher <inline-formula><tex-math notation="LaTeX">$\delta$</tex-math></inline-formula> enables unique state reconstruction despite the presence of more compromised sensors. In this study, for undirected multi-agent systems consisting of <inline-formula><tex-math notation="LaTeX">$ n$</tex-math></inline-formula> agents, we analyze the relationship between the number of agents <inline-formula><tex-math notation="LaTeX">$ n$</tex-math></inline-formula> and the sparse observability index <inline-formula><tex-math notation="LaTeX">$ \delta$</tex-math></inline-formula> for effective secure state estimation. In particular, we consider four typical graph structures: path, cycle, complete, and complete bipartite graphs. Our analysis reveals that <inline-formula><tex-math notation="LaTeX">$\delta$</tex-math></inline-formula> does not increase monotonically with <inline-formula><tex-math notation="LaTeX">$n$</tex-math></inline-formula>, and that resilience is intricately tied to the underlying network structure. Notably, we demonstrate that the system exhibits enhanced resilience when the number of agents <inline-formula><tex-math notation="LaTeX">$n$</tex-math></inline-formula> is a prime number, although the specifics of this relationship vary depending on the graph topology.
ISSN:2694-085X