  The Hankel-norm approximation is a model reduction method which provides the
best approximation in the Hankel semi-norm. In this paper the computation of
the optimal Hankel-norm approximation is generalized to the case of linear
time-invariant continuous-time descriptor systems. An efficient algorithm is
developed by refining the generalized balanced truncation square root method.
For a wide practical usage, adaptations of the introduced algorithm towards
stable computations and sparse systems are made as well as an approach for a
projection-free algorithm. To show the approximation behavior of the introduced
method, numerical examples are presented.
