Coordination in networks of linear impulsive agents

The paper focuses on consensus in heterogeneous networks containing both linear and linear impulsive dynamics. This model applies for networks that are formed by several clusters. Most agents can only update their state in a continuous way using inner-cluster agent states. On top of this, few agents also have the peculiarity to update their states in a discrete way by reseting it using states from agents outside their clusters. The motivation of this behavior is that communication constraints hamper continuous inter-clusters interactions. Under appropriate assumptions we prove that all subsystems asymptotically agree and we provide an upper-bound of the convergence speed. We illustrate the behavior with an academic example containing five agents grouped in two clusters.