Performance of Leader-Follower Coherence for Selecting Leaders Using Node Centrality Indices

This brief investigates a leader selection problem within leader-follower consensus systems based on node centrality indices. The performance of leader-follower networks is characterized in terms of its coherence quantified by the eigenvalues of the principal submatrix derived from the Laplacian matrix. To obtain exact connections between leaders selected by node centrality indices and coherence, a family of deterministic networks are employed as network models. Our findings reveal that the performance of leader-follower coherence is determined by the selected leaders. A leader node with greater centrality leads to improved coherence. It is numerically verified by a random network model, highlighting the impact of network topology on coherence.