  In this paper, we utilize information theory to study the fundamental
performance limitations of generic feedback systems, where both the controller
and the plant may be any causal functions/mappings while the disturbance can be
with any distributions. More specifically, we obtain fundamental
$\mathcal{L}_p$ bounds on the control error, which are shown to be completely
characterized by the conditional entropy of the disturbance, based upon the
entropic laws that are inherent in any feedback systems. We also discuss the
generality and implications (in, e.g., fundamental limits of learning-based
control) of the obtained bounds.
