  In this paper we address the problem of information-constrained optimal
control for an interconnected system subject to one-step communication delays
and power constraints. The goal is to minimize a finite-horizon quadratic cost
by optimally choosing the control inputs for the subsystems, accounting for
power constraints in the overall system and different information available at
the decision makers. To this purpose, due to the quadratic nature of the power
constraints, the LQG problem is reformulated as a linear problem in the
covariance of state-input aggregated vector. The zero-duality gap allows us to
equivalently consider the dual problem, and decompose it into several
sub-problems according to the information structure present in the system.
Finally, the optimal control inputs are found in a form that allows for offline
computation of the control gains.
