Dynamic Event-Triggered Consensus of Multi-agent Systems on Matrix-weighted Networks
Pan, Lulu, Shao, Haibin, Li, Dewei, Liu, Lin
–arXiv.org Artificial Intelligence
Although the consensus problem has been extensively investigated, the ties among agents are assumed to be characterized by scalar-weighted networks, which fail in characterizing interdependencies among higher-dimensional states of neighboring agents. Recently, a broader category of networks termed matrix-weighted networks has been introduced which is an immediate generalization of scalar-weighted networks Sun and Yu [27], Pan et al. [23, 20], Trinh et al. [28], Pan et al. [21, 22], Wang et al. [30], Pan et al. [19]. In fact, matrix-weighted networks naturally become relevant in scenarios such as graph effective resistance based distributed control and estimation Barooah and Hespanha [2], logical inter-dependency of multiple topics in opinion evolution Friedkin et al. [8], bearing-based formation control Zhao and Zelazo [37], array of coupled LC oscillators Tuna [29] as well as consensus and synchronization on matrix-weighted networks Trinh et al. [28], Pan et al. [20]. As opposed to scalar-weighted networks, connectivity alone does not translate to achieving consensus for matrixweighted networks. To this end, properties of weight matrices play an important role in characterizing consensus. For instance, positive definiteness and positive semi-definiteness of weight matrices have been employed to provide consensus conditions in Trinh et al. [28]; negative definiteness and negative semi-definiteness of weight matrices
arXiv.org Artificial Intelligence
Sep-4-2022
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