  Stochastic thermodynamics lays down a broad framework to revisit the
venerable concepts of heat, work and entropy production for individual
stochastic trajectories of mesoscopic systems. Remarkably, this approach,
relying on stochastic equations of motion, introduces time into the description
of thermodynamic processes -- which opens the way to fine control them. As a
result, the field of finite-time thermodynamics of mesoscopic systems has
blossomed. In this article, after introducing a few concepts of control for
isolated mechanical systems evolving according to deterministic equations of
motion, we review the different strategies that have been developed to realize
finite-time state-to-state transformations in both over and underdamped
regimes, by the proper design of time-dependent control parameters/driving. The
systems under study are stochastic, epitomized by a Brownian object immersed in
a fluid; they are thus strongly coupled to their environment playing the role
of a reservoir. Interestingly, a few of those methods (inverse engineering,
counterdiabatic driving, fast-forward) are directly inspired by their
counterpart in quantum control. The review also analyzes the control through
reservoir engineering. Besides the reachability of a given target state from a
known initial state, the question of the optimal path is discussed. Optimality
is here defined with respect to a cost function, a subject intimately related
to the field of information thermodynamics and the question of speed limit.
Another natural extension discussed deals with the connection between arbitrary
states or non-equilibrium steady states. This field of control in stochastic
thermodynamics enjoys a wealth of applications, ranging from optimal mesoscopic
heat engines to population control in biological systems.
