  The closed-loop stability and infinite-horizon performance of
receding-horizon approximations are studied for non-stationary linear-quadratic
regulator (LQR) problems. The approach is based on a lifted reformulation of
the optimal control problem, under assumed uniform controllability and
observability, leading to a strict contraction property of the corresponding
Riccati operator. Leveraging this contraction property, a stabilizing linear
time-varying state-feedback approximation of the infinite-horizon optimal
control policy is constructed to meet a performance-loss specification. Its
synthesis involves only finite preview of the time-varying problem data at each
time step, over a sufficiently long prediction horizon.
