Robust mean square stability

In this paper, we formalize the Robust Mean Square Stability problem in the presence of deterministic LTI perturbations. In particular, we extend the robust stability notion of
$\mu$
to include both deterministic and stochastic uncertainties and provide a computable sufficient condition that guarantees Robust Mean Square Stability of the closed-loop. We use an inverted pendulum example where the sensor is subject to link/attention dropout and find the trade-off between the amount of attention and fragility to model uncertainty expressed as the size of the disk margin.