  Controlling infinite dimensional models remains a challenging task for many
practitioners since they are not suitable for traditional control design
techniques or will result in a high-order controller too complex for
implementation. Therefore, the model or the controller need to be reduced to an
acceptable dimension, which is time-consuming, requires some expertise and may
introduce numerical error. This paper tackles the control of such a system,
namely a continuous crystallizer, and compares two different data-driven
strategies: the first one is a structured robust technique while the other one,
called L-DDC, is based on the Loewner interpolatory framework.
