  The objective of model reference control is to design a controller that
regulates the system's behavior so as to match the behavior of a specified
reference model. This paper investigates necessary and sufficient conditions
for model reference control from a data-driven perspective, when only a set of
data generated by the system is utilized to directly accomplish the matching.
Noiseless and noisy data cases are both considered. Notably, all methods we
propose build on the concept of data informativity and do not rely on
persistently exciting data.
