  The Loewner framework for model reduction is extended to the class of linear
switched systems. One advantage of this framework is that it introduces a
trade-off between accuracy and complexity. Moreover, through this procedure,
one can derive state-space models directly from data which is related to the
input-output behavior of the original system. Hence, another advantage of the
framework is that it does not require the initial system matrices. More
exactly, the data used in this framework consists in frequency domain samples
of input-output mappings of the original system. The definition of generalized
transfer functions for linear switched systems resembles the one for bilinear
systems. A key role is played by the coupling matrices, which ensure the
transition from one active mode to another.
