  Data-driven predictive control (DPC) has recently gained popularity as an
alternative to model predictive control (MPC). Amidst the surge in proposed DPC
frameworks, upon closer inspection, many of these frameworks are more closely
related (or perhaps even equivalent) to each other than it may first appear. We
argue for a more formal characterization of these relationships so that results
can be freely transferred from one framework to another, rather than being
uniquely attributed to a particular framework. We demonstrate this idea by
examining the connection between $\gamma$-DDPC and the original DeePC
formulation.
