  Much of the current theory of networked control systems uses simple
point-to-point communication models as an abstraction of the underlying
network. As a result, the controller has very limited information on the
network conditions and performs suboptimally. This work models the underlying
wireless multihop mesh network as a graph of links with transmission success
probabilities, and uses a recursive Bayesian estimator to provide packet
delivery predictions to the controller. The predictions are a joint probability
distribution on future packet delivery sequences, and thus capture correlations
between successive packet deliveries. We look at finite horizon LQG control
over a lossy actuation channel and a perfect sensing channel, both without
delay, to study how the controller can compensate for predicted network
outages.
