  Schur-type methods in \cite{Chu2} and \cite{GCQX} solve the robust pole
assignment problem by employing the departure from normality of the closed-loop
system matrix as the measure of robustness. They work well generally when all
poles to be assigned are simple. However, when some poles are close or even
repeated, the eigenvalues of the computed closed-loop system matrix might be
inaccurate. In this paper, we present a refined Schur method, which is able to
deal with the case when some or all of the poles to be assigned are repeated.
More importantly, the refined Schur method can still be applied when
\verb|place| \cite{KNV} and \verb|robpole| \cite{Tits} fail to output a
solution when the multiplicity of some repeated poles is greater than the input
freedom.
