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Journal ArticleDOI

Consensus Problems on Networks With Antagonistic Interactions

TLDR
The question asked in this paper is: is it possible to achieve a form of agreement also in presence of antagonistic interactions, modeled as negative weights on the communication graph?
Abstract
In a consensus protocol an agreement among agents is achieved thanks to the collaborative efforts of all agents, expresses by a communication graph with nonnegative weights. The question we ask in this paper is the following: is it possible to achieve a form of agreement also in presence of antagonistic interactions, modeled as negative weights on the communication graph? The answer to this question is affirmative: on signed networks all agents can converge to a consensus value which is the same for all agents except for the sign. Necessary and sufficient conditions are obtained to describe cases in which this is possible. These conditions have strong analogies with the theory of monotone systems. Linear and nonlinear Laplacian feedback designs are proposed.

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Citations
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Journal ArticleDOI

Recent Advances in Consensus of Multi-Agent Systems: A Brief Survey

TL;DR: Focusing on different kinds of constraints on the controller and the self-dynamics of each individual agent, as well as the coordination schemes, the recent results are categorized into consensus with constraints, event-based consensus, consensus over signed networks, and consensus of heterogeneous agents.
Journal ArticleDOI

A tutorial on modeling and analysis of dynamic social networks. Part I

TL;DR: The aim of this tutorial is to highlight a novel chapter of control theory, dealing with applications to social systems, to the attention of the broad research community.
Journal ArticleDOI

On the consensus and bipartite consensus in high-order multi-agent dynamical systems with antagonistic interactions

TL;DR: The aim of this paper is to address consensus and bipartite consensus for a group of homogeneous agents, under the assumption that their mutual interactions can be described by a weighted, signed, connected and structurally balanced communication graph.
Journal ArticleDOI

Interval Bipartite Consensus of Networked Agents Associated With Signed Digraphs

TL;DR: It is shown that all agents reach interval bipartite consensus if their associated signed digraph has a spanning tree, and the consensus values of all agents depend only on the initial states of those agents which are associated with root vertices.
Journal ArticleDOI

A survey on recent advances in distributed sampled-data cooperative control of multi-agent systems

TL;DR: A survey on recent advances in distributed cooperative control under a sampled-data setting, with special emphasis on the published results since 2011, and several challenging issues for future research are proposed.
References
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Journal ArticleDOI

Social Network Analysis: Methods and Applications.

TL;DR: This work characterizes networked structures in terms of nodes (individual actors, people, or things within the network) and the ties, edges, or links that connect them.
Journal ArticleDOI

Consensus problems in networks of agents with switching topology and time-delays

TL;DR: A distinctive feature of this work is to address consensus problems for networks with directed information flow by establishing a direct connection between the algebraic connectivity of the network and the performance of a linear consensus protocol.
Proceedings ArticleDOI

Flocks, herds and schools: A distributed behavioral model

TL;DR: In this article, an approach based on simulation as an alternative to scripting the paths of each bird individually is explored, with the simulated birds being the particles and the aggregate motion of the simulated flock is created by a distributed behavioral model much like that at work in a natural flock; the birds choose their own course.
Book

Nonnegative Matrices in the Mathematical Sciences

TL;DR: 1. Matrices which leave a cone invariant 2. Nonnegative matrices 3. Semigroups of non negative matrices 4. Symmetric nonnegativeMatrices 5. Generalized inverse- Positivity 6. M-matrices 7. Iterative methods for linear systems 8. Finite Markov Chains
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