  An important aspect in jointly analysing networked control systems and their
communication is to model the networking in a sufficiently rich but at the same
time mathematically tractable way. As such, this paper improves on a recently
proposed scalable approach for analysing multi-agent systems with stochastic
packet loss by allowing for heterogeneous transmission probabilities and
temporal correlation in the communication model. The key idea is to consider
the transmission probabilities as uncertain, which facilitates the use of tools
from robust control. Due to being formulated in terms of linear matrix
inequalities that grow linearly with the number of agents, the result is
applicable to very large multi-agent systems, which is demonstrated by
numerical simulations with up to 10000 agents.
