期刊
IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING
卷 9, 期 3, 页码 1264-1281出版社
IEEE COMPUTER SOC
DOI: 10.1109/TNSE.2021.3139045
关键词
Network topology; Multi-agent systems; Costs; Resilience; Topology; Eigenvalues and eigenfunctions; Consensus algorithm; Coordination; distributed control; multi-agent systems; trust-based consensus
资金
- Young Researchers Career Development Project-training of doctoral students of the Croatian Science Foundation - European Union from the European Social Fund
- EU-ICT Project ASSISIbf -Animal and robot Societies Self-organise and Integrate by Social Interaction bees and fish [601074]
- EU-ICT Project WatchPlant -Smart Biohybrid PhytoOrganisms for Environmental In Situ Monitoring [101017899]
- EU-ICT Project AeRoTwin -Twinning coordination action for spreading excellence in Aerial Robotics [810321]
This paper addresses a distributed connectivity control problem and proposes a method based on algebraic connectivity measure. The method estimates the algebraic connectivity locally and controls the network topology through a control strategy. Experimental results demonstrate the effectiveness of the proposed method.
This paper addresses a distributed connectivity control problem in networked multi-agent systems. The system communication topology is controlled through the algebraic connectivity measure, the second smallest eigenvalue of the communication graph Laplacian. The algebraic connectivity is estimated locally in a decentralized manner through a trust-based consensus algorithm, in which the agents communicate the perceived quality of the communication links in the system with their set of neighbors. In the presented approach, link qualities represent the weights of the communication graph from which the adjacency matrix is estimated. The Laplacian matrix and its eigenvalues, including the algebraic connectivity, are then calculated from this local estimate of the global adjacency matrix. A method for network topology control is proposed, which creates and deletes communication links based on the Albert-Barabasi probabilistic model, depending on the estimated and referenced connectivity level. The proposed algebraic connectivity estimation and connectivity maintenance strategy have been validated both in simulation and on a physical robot swarm, demonstrating the method performance under varying initial topology of the communication graph, different multi-agent system sizes, in various deployment scenarios, and in the case of agent failure.
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