  Time domain identification is studied in this paper for parameters of a
continuous-time multi-input multi-output descriptor system, with these
parameters affecting system matrices through a linear fractional
transformation. Sampling is permitted to be slow and non-uniform, and there are
no necessities to satisfy the Nyquist frequency restrictions. This model can be
used to described the behaviors of a networked dynamic system, and the obtained
results can be straightforwardly applied to an ordinary state-space model, as
well as a lumped system. An explicit formula is obtained respectively for the
transient and steady-state responses of the system stimulated by an arbitrary
signal. Some relations have been derived between the system steady-state
response and its transfer function matrix (TFM), which reveal that the value of
a TFM at any interested point, as well as its derivatives, can in principle be
estimated from input-output experimental data. Based on these relations, an
estimation algorithm is suggested respectively for the parameters of the
descriptor system and the values of its TFM. Their properties like asymptotic
unbiasedness, consistency, etc., are analyzed.
