Detection of Abnormal Nodes in Clustered Control Systems Based on Multiagent Group Prominence Analyses

In now networked control systems, some nodes may be invaded and become abnormal which may tamper with the execution of tasks; especially, in clustered networked control systems, the nodes are hierarchical and hybrid, thus the detection of abnormal nodes is difficult. To deal with such problem, this paper uses the multiagent method to model and analyze the clustered control systems, where the cluster stations and control units are modeled as the coalition systems of hybrid agents. Based on the multiagent model, then the paper presents the concept of group prominence to measure the strategy characteristics of cluster stations and control units; finally, a model for detecting abnormal nodes based on multiagent group prominence analyses is presented, which can effectively improve the consistency of the system.

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