  This text aims at providing a bird's eye view of system identification with
special attention to nonlinear systems. The driving force is to give a feeling
for the philosophical problems facing those that build mathematical models from
data. Special attention will be given to grey-box approaches in nonlinear
system identification. In this text, grey-box methods use auxiliary information
such as the system steady-state data, possible symmetries, some bifurcations
and the presence of hysteresis. The text ends with a sample of applications. No
attempt is made to be thorough nor to survey such an extensive and mature field
as system identification. In most parts references will be provided for a more
detailed study.
