  A wide variety of complex systems exhibit large fluctuations both in space
and time that often can be attributed to the presence of some kind of critical
phenomena. Under such critical scenario it is well known that the properties of
the correlation functions in space and time are two sides of the same coin.
Here we test wether systems exhibiting a phase transition could self-tune to
its critical point taking advantage of such correlation properties. We describe
results in three models: the 2D Ising ferromagnetic model, the 3D Vicsek
flocking model and a small-world neuronal network model. We illustrate how the
feedback of the autocorrelation function of the order parameter fluctuations is
able to shift the system towards its critical point. Since the results rely on
universal properties they are expected to be relevant to a variety of other
settings.
