  Over the past two decades, there has been a growing interest in control
systems research to transition from model-based methods to data-driven
approaches. In this study, we aim to bridge a divide between conventional
model-based control and emerging data-driven paradigms grounded in Willem's
fundamental lemma. Specifically, we study how input/output data from two
separate systems can be manipulated to represent the behavior of interconnected
systems, either connected in series or through feedback. Using these results,
this paper introduces the Internal Behavior Control (IBC), a new control
strategy based on the well-known Internal Model Control (IMC) but viewed under
the lens of Behavioral System Theory. Similar to IMC, the IBC is easy to tune
and results in perfect tracking and disturbance rejection but, unlike IMC, does
not require a parametric model of the dynamics. We present two approaches for
IBC implementation: a component-by-component one and a unified one. We compare
the two approaches in terms of filter design, computations, and memory
requirements.
