Sparsest Minimum Multiple-Cost Structural Leader Selection ?

摘要

In this paper, we address the problem of leader selection in a network of agents when the input signal can originate from different sources (for instance communication/control towers) and incur different costs. We assume that each agent's state is defined by a scalar that evolves according to linear dynamics involving the states of its neighbors and its own state. We propose an algorithm to determine the minimum number of agents that should behave as leaders (i.e., agents whose states serve as references (or inputs) to the remaining agents-the followers), while incurring the lowest cost. Finally, illustrative examples using the main results of the paper are provided.