학술논문

Identifying Disconnected Agents in Multiagent Systems via External Estimators
Document Type
Periodical
Source
IEEE Transactions on Cybernetics IEEE Trans. Cybern. Cybernetics, IEEE Transactions on. 54(2):1011-1023 Feb, 2024
Subject
Signal Processing and Analysis
Communication, Networking and Broadcast Technologies
Robotics and Control Systems
General Topics for Engineers
Components, Circuits, Devices and Systems
Computing and Processing
Power, Energy and Industry Applications
Multi-agent systems
Time series analysis
Eigenvalues and eigenfunctions
Communication networks
Telecommunications
Graph theory
Convergence
Connectivity
consensus analysis
estimation
multiagent systems
time-series analysis
Language
ISSN
2168-2267
2168-2275
Abstract
This article addresses the problem of identifying disconnected agents in multiagent systems via external estimators. Specifically, we employ external estimators with an appropriately designed decision rule to identify the disconnectedness (i.e., the status of being disconnected) between two arbitrarily chosen agents in formation-control multiagent systems. The design of the decision rule is inspired by the unit-root testing problem of autoregressive time series. To make the best possible decision, a best-effort procedure is also proposed. Then, by introducing the concept of connected components (or just components) in graph theory, and using the methods of consensus analysis and time-series analysis, we develop an analytical framework to show the theoretical performance of the designed decision rule. A particularly important result shown by our analysis is that the miss probability of the decision rule can converge to 0 as the number of data samples increases. Finally, simulation results validate the performance of the decision rule and the best-effort procedure, showing that they can perform well even in small samples.