  This paper presents a data-driven solution to the discrete-time infinite
horizon LQR problem. The state feedback gain is computed directly from a batch
of input and state data collected from the plant. Simulation examples
illustrate the convergence of the proposed solution to the optimal LQR gain as
the number of Markov parameters tends to infinity. Experiments in an
uninterruptible power supply are presented, which demonstrate the practical
applicability of the design methodology.
