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Networked Multiagent Systems: Antagonistic Interaction, Constraint, and its Application

Wentao Zhang, Zhiqiang Zuo, Yijing Wang

2021IEEE Transactions on Neural Networks and Learning Systems23 citationsDOI

Abstract

In this article, we study the consensus problem in the framework of networked multiagent systems with constraint where there exists antagonistic information. A major difficulty is how to characterize the communication among the interacting agents in the presence of antagonistic information without resorting to the signed graph theory, which plays a central role in the Altafini model. It is shown that the proposed control protocol enables us to solve the consensus problem in a node-based viewpoint where both cooperative and antagonistic interactions coexist. Moreover, the proposed setup is further extended to the case of input saturation, leading to the semiglobal consensus. In addition, the consensus region associated with antagonistic information among participating individuals is also elaborated. Finally, the deduced theoretical results are applied to the task distribution problem via unmanned ground vehicles.

Topics & Concepts

Constraint (computer-aided design)Multi-agent systemComputer scienceConsensusProtocol (science)Distributed computingGraphNode (physics)Task (project management)Theoretical computer scienceArtificial intelligenceMathematicsEngineeringPathologySystems engineeringGeometryStructural engineeringMedicineAlternative medicineDistributed Control Multi-Agent SystemsNeural Networks Stability and SynchronizationStability and Control of Uncertain Systems
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