SYSYAug 23, 2017

On Non-Consensus Motions of Dynamical Linear Multi-Agent Systems

arXiv:1708.069331 citations
AI Analysis

For researchers in multi-agent systems, this work provides a systematic classification of non-consensus behaviors, but it is incremental as it extends known consensus conditions to non-consensus scenarios.

This paper analyzes mechanisms causing non-consensus motions in high-order linear multi-agent systems, classifying non-consensus phases based on agent dynamics, interaction protocols, and graph topology. Numerical examples validate the theoretical analysis.

The non-consensus problems of high order linear time-invariant dynamical homogeneous multi-agent systems are concerned. Based on the conditions of consensus achievement, the mechanisms that lead to non-consensus motions are analyzed. Besides, a comprehensive classification for diverse types of non-consensus phases in accordance to the different conditions is conducted, which is jointly depending on the self-dynamics of agents, the interactive protocol and the graph topology. A series of numerical examples are demonstrated to illustrate the theoretical analysis.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

Your Notes