Cluster Consensus in Networks of Agents With Weighted Cooperative–Competitive Interactions

Zhan, Jingyuan; Li, Xiang

doi:10.1109/tcsii.2017.2713526

Cited by 58 publications

(41 citation statements)

References 20 publications

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“…To cope with the unanticipated situations or changes, clustering scenarios (e.g., Refs. [20][21][22]) have received considerable attention. Therein, a great deal headway has been made for the cluster/group consensus problems in cooperative-competitive network, while the antagonistic relations only exist between different subnetworks in MASs.…”

Section: Introductionmentioning

confidence: 99%

Distributed multiple-bipartite consensus in networked Lagrangian systems with cooperative-competitive interactions

Zhang

et al. 2021

Preprint

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In combination with the collective behavior evolutions of bipartite consensus and cluster/group consensus, this paper proposes the notion of multiple-bipartite consensus in networked Lagrangian systems (NLSs). The distributed leaderless and leader-following multiple-bipartite consensus control laws for NLSs are presented in the cooperative-competitive network, where the negative interactions between agents can exist in the same subnetwork. By introducing an acyclic partition and adding the integral item in the control protocols, the final explicit convergence states in the leaderless case are eventually obtained. Moreover, the leader-following scenario can be realized in fifinite time with integrated controllers. All of the effectiveness has been illustrated through numerical simulations.

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Section: Introductionmentioning

confidence: 99%

Distributed multiple-bipartite consensus in networked Lagrangian systems with cooperative-competitive interactions

Zhang

et al. 2021

Preprint

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“…In fact, consensus can be seen as the core dynamical behavior of multi-agent networks due to the decisive effect of coupling interactions among agents. Cluster consensus has been extensively considered in abundant previous works [33][34][35]. For example, cluster consensus of second-order multi-agent systems is investigated in [36] by pinning control technique.…”

Section: Introductionmentioning

confidence: 99%

New methods to realize the cluster consensus for multi‐agent networks

Guo

Liang

Fardoun

2019

Asian Journal of Control

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This paper investigates the cluster consensus problem for multi-agent networks via a new method. Firstly, a distributed cluster consensus protocol is proposed by constructing a new Laplacian matrix, which is not required to be row-zero-sum. It is shown that the cluster consensus of directed multi-agent networks can be achieved under the presented protocol, and the final cluster consensus values of the considered system are also given in this paper, which only depend on the initial states of all agents. Next, a pinning cluster consensus law is provided to force the dynamics of the agents to the desired trajectory. Furthermore, it is found that the cluster consensus of directed networks can be reached even in presence of arbitrary finite communication delays. Finally, effectiveness of the obtained results is demonstrated by numerical examples.

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“…It has been revealed that structural balance property is a key factor in causing the failure of consensus, e.g., see [6], [14], [21]- [23]. The opinion disagreement could be in form of bipartite/polarized consensus [14], several clustered groups [15] or divergence [24] depending on different dynamics adopted. However, structural balance theory does not give a clear explanation of the opinion divergence in structurally unbalanced social networks.…”

Section: Introductionmentioning

confidence: 99%

A Novel Interpretation for Opinion Consensus in Social Networks With Antagonisms

Yang

Song

2019

IEEE Access

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We take a new perspective for the consensus in DeGroot-type social networks with antagonistic interactions between some pairs of agents. We observe the analogies between social networks and electrical networks. A line with positive (or negative) conductance in the electrical network well corresponds to the cooperative (or antagonistic) interaction in the social network. Then, we introduce a refined definition of effective conductance (EC), which comes from electrical networks, into social networks as a characterization of the overall relationship between a pair of agents. The EC considers the effects of both direct and indirect interactions between the agents. Some EC-based consensus criteria are established by analytical and statistical approaches, showing that the sign of EC is a useful indicator of consensus. The opinion consensus can be generally interpreted as every pair of agents being overall cooperative despite antagonistic interactions, i.e., the corresponding EC being positive. The obtained results provide new insights into the consensus mechanism with clear intuition. Case study of a 15-agent network is provided as an illustration.

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Cluster Consensus in Networks of Agents With Weighted Cooperative–Competitive Interactions

Cited by 58 publications

References 20 publications

Distributed multiple-bipartite consensus in networked Lagrangian systems with cooperative-competitive interactions

Distributed multiple-bipartite consensus in networked Lagrangian systems with cooperative-competitive interactions

New methods to realize the cluster consensus for multi‐agent networks

A Novel Interpretation for Opinion Consensus in Social Networks With Antagonisms

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