Dynamic Average Consensus based on Group Information for Multi-Swarm Systems

This paper deals with distributed protocols to track the time-varying average of a dynamic Multi-Swarm System (MSS) using group information. To solve the swarm average consensus problem, the agents of each swarm can exchange information at the intra-swarm level. However, only one agent of each swarm, referred to as the swarm communicating agent, can share its group information with the other swarms. We show that the discrete time protocols asymptotically achieve consensus on the dynamic swarm average with a bounded error. The algorithms are developed for both fixed and switching communicating agents configurations with strongly connected and weighted balanced directed graphs. We provide numerical simulations to illustrate the efficiency of our solutions.