In Chaps. 7–9, the disagreement behaviors, especially the fluctuation behaviors, have been disclosed for signed networks subject to switching topologies, which, however, only focuses on the overall state evolutions of signed networks. As a result, the specific disagreement behaviors of local agents may not be well observed. Motivated by the hierarchical structure decomposition developed for fixed signed networks in Chap. 6, we may also establish a similar hierarchical structure decomposition for switching signed networks based on the local simultaneous structural balance of agents to explore the local disagreement characterizations of them. In this chapter, the extended structural balance theory is developed by concerning the “local nodes” instead of global signed digraphs, which is realized by proposing the notion of simultaneously structurally balanced nodes. This, together with the extended leader–follower framework, leads to a role identification framework for switching signed networks. Consequently, the local disagreement behaviors of agents can be revealed through the role identifications of them such that more specific disagreement behaviors for switching signed networks can be obtained. It is shown that for any switching signed networks, the simultaneously structurally balanced agents, especially the simultaneously structurally balanced union leaders, dominate the state evolutions of all agents. In particular, the quasi-interval bipartite consensus behavior for jointly quasi-strongly connected signed networks is more specifically characterized by disclosing the equivalence between the impact index of union leaders and the number of simultaneously structurally balanced agents. Two simulation examples are provided to illustrate the local disagreement behavior characterizations for signed networks with switching topologies.


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    Titel :

    Local Characterization of Fluctuation Behaviors


    Weitere Titelangaben:

    Intelligent Control & Learning Systems


    Beteiligte:
    Meng, Deyuan (Autor:in) / Du, Mingjun (Autor:in) / Wu, Yuxin (Autor:in)


    Erscheinungsdatum :

    2022-12-03


    Format / Umfang :

    17 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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