  This paper studies the finite-horizon linear quadratic regulation problem
where the dynamics of the system are assumed to be unknown and the state is
accessible. Information on the system is given by a finite set of input-state
data, where the input injected in the system is persistently exciting of a
sufficiently high order. Using data, the optimal control law is then obtained
as the solution of a suitable semidefinite program. The effectiveness of the
approach is illustrated via numerical examples.
