  This paper studies an output feedback stabilization control framework for
discrete-time linear systems with stochastic dynamics determined by an
independent and identically distributed (i.i.d.) process. The controller is
constructed with an ensemble Kalman filter (EnKF) and a feedback gain designed
with our earlier result about state feedback control. The EnKF is also used for
modeling the distribution behind the system, which is required in the feedback
gain synthesis. The effectiveness of our control framework is demonstrated with
numerical experiments. This study will become the first step toward the
realization of learning type control using our stochastic systems control
theory.
