The aim of this chapter is to recall that the corpus of the control theory is a now quite established domain of knowledge which is mainly dedicated to mitigate the effect of uncertainties in dynamical systems. As such, control theory provides many concepts and tools that are worth to keep in mind should one be intended to design a feedback control law for a nonlinear dynamical system involving a high level of uncertainties. The chapter uses some illustrative examples to assess this message and gives some specific control design methods and their associated closed-loop-related results. Some of these schemes are extensively used in some of the use-cases discussed in the third part of the book. The ambition of this short chapter is not to give an overview of all existing tricks and methods that have been invented during decades of research on control systems theory, but simply to recall that for a class of regulation/tracking problems, standard approaches might never be surpassed by so-called smart or data-driven design approaches. This makes knowing standard approaches mandatory for an optimal handling of such problems. In other words, this chapter is a kind of teaser that should incite the interested reader to consult the control-related textbooks that might give their solutions a control-specific flavor that might be crucial to their success.