  We propose a provably stabilizing and tractable approach for control of
constrained linear systems under intermittent observations and unreliable
transmissions of control commands. A smart sensor equipped with a Kalman filter
is employed for the estimation of the states from incomplete and corrupt
measurements, and an estimator at the controller side optimally feeds the
intermittently received sensor data to the controller. The remote controller
iteratively solves constrained stochastic optimal control problems and
transmits the control commands according to a carefully designed transmission
protocol through an unreliable channel. We present a (globally) recursively
feasible quadratic program, which is solved online to yield a stabilizing
controller for Lyapunov stable linear time invariant systems under any positive
bound on control values and any non-zero transmission probabilities of
Bernoulli channels.
