Robust mean square stability

Yuanji Zou, Nicola Elia

Abstract: 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.