Distributed Average Consensus in Open Multi-Agent Systems

In this paper, we consider the problem of distributed average consensus in multi-agent systems, where each agent can come in or move out of the system, possibly multiple times. In the literature, such systems are referred to as open multi-agent systems. A typical goal in such settings is to use an iterative distributed algorithm to calculate the average of some quantities of interest each agent possesses, which can be crucial in many estimation, control, or optimization applications. We consider an open multi-agent setting and propose a distributed algorithm that allows the participating agents to track their average. More specifically, if the set of agents remaining in the computation eventually settles to a certain subset of agents, then the proposed algorithm allows them (under some mild connectivity conditions) to asymptotically reach consensus to the average of the quantities of interest these remaining agents hold. Analysis and numerical examples to illustrate the operation of the proposed algorithm are also provided.