  We design the controls of physical systems that are faced by uncertainties.
The system dynamics are described by random hyperbolic balance laws. The
control aims to steer the system to a desired state under uncertainties. We
propose a control based on Lyapunov stability analysis of a suitable series
expansion of the random dynamics. The control damps the impact of uncertainties
exponentially fast in time. The presented approach can be applied to a large
class of physical systems and random perturbations, as e.g. Gaussian processes.
We illustrate the control effect on a stochastic viscoplastic material model.
