  Multiagent systems consist of agents that locally exchange information
through a physical network subject to a graph topology. Current control methods
for networked multiagent systems assume the knowledge of graph topologies in
order to design distributed control laws for achieving desired global system
behaviors. However, this assumption may not be valid for situations where graph
topologies are subject to uncertainties either due to changes in the physical
network or the presence of modeling errors especially for multiagent systems
involving a large number of interacting agents. Motivating from this
standpoint, this paper studies distributed control of networked multiagent
systems with uncertain graph topologies. The proposed framework involves a
controller architecture that has an ability to adapt its feed- back gains in
response to system variations. Specifically, we analytically show that the
proposed controller drives the trajectories of a networked multiagent system
subject to a graph topology with time-varying uncertainties to a close
neighborhood of the trajectories of a given reference model having a desired
graph topology. As a special case, we also show that a networked multi-agent
system subject to a graph topology with constant uncertainties asymptotically
converges to the trajectories of a given reference model. Although the main
result of this paper is presented in the context of average consensus problem,
the proposed framework can be used for many other problems related to networked
multiagent systems with uncertain graph topologies.
