Archetypal stick balancing task represents a wide class of unstable processes under human control. The currently dominant theory of human control in stick balancing is based on the concept of discontinuous, or intermittent control. Traditionally, intermittent control models involve threshold-driven control activation, however, recently it has been demonstrated that, in a simple virtual stick balancing task, some basic properties of human control activation mechanisms can only be reflected by more sophisticated, noise-driven models. The aim of the present paper is to demonstrate that the previously introduced double-well model of noise-driven intermittent control activation can reproduce the experimentally observed human behaviours under various conditions. We show that the model successfully reproduces the experimental distributions of actions points (stick angle values triggering activation of human control) obtained in two previously reported experiments. Moreover, we show that a slight change in the model's noise intensity parameter leads to a sudden shift of model distributions, that is, a non-equilibrium phase transition is observed. Our results extend the current understanding of the concept of noise-driven control activation, suggesting that it is applicable in a variety of experimental setups. The two discovered phases of the double-well model correspond to two different modes of control activation in human operators; physiological basis of these modes has to be investigated in future studies.