  This work addresses the finite-horizon robust covariance control problem for
discrete-time, partially observable, linear system affected by random zero mean
noise and deterministic but unknown disturbances restricted to lie in what is
called ellitopic uncertainty set (e.g., finite intersection of centered at the
origin ellipsoids/elliptic cylinders). Performance specifications are imposed
on the random state-control trajectory via averaged convex quadratic
inequalities, linear inequalities on the mean, as well as pre-specified upper
bounds on the covariance matrix. For this problem we develop a computationally
tractable procedure for designing affine control policies, in the sense that
the parameters of the policy that guarantees the aforementioned performance
specifications are obtained as solutions to an explicit convex program. Our
theoretical findings are illustrated by a numerical example.
