Gradient methods for iterative distributed control synthesis
In this paper we present a gradient method to iteratively update local controllers of a distributed linear system driven by stochastic disturbances. The control objective is to minimize the sum of the variances of states and inputs in all nodes. We show that the gradients of this objective can be estimated distributively using data from a forward simulation of the system model and a backward simul