  The ability to robustly and efficiently control the dynamics of nonlinear
systems lies at the heart of many current technological challenges, ranging
from drug delivery systems to ensuring flight safety. Most such scenarios are
too complex to tackle directly and reduced-order modelling is used in order to
create viable representations of the target systems. The simplified setting
allows for the development of rigorous control theoretical approaches, but the
propagation of their effects back up the hierarchy and into real-world systems
remains a significant challenge. Using the canonical setup of a liquid film
falling down an inclined plane under the action of active feedback controls in
the form of blowing and suction, we develop a multi-level modelling framework
containing both analytical models and direct numerical simulations acting as an
in silico experimental platform. Constructing strategies at the inexpensive
lower levels in the hierarchy, we find that offline control transfer is not
viable, however analytically-informed feedback strategies show excellent
potential, even far beyond the anticipated range of applicability of the
models. The detailed effects of the controls in terms of stability and
treatment of nonlinearity are examined in detail in order to gain understanding
of the information transfer inside the flows, which can aid transition towards
other control-rich frameworks and applications.
