  We address robustness issues of self-triggered sampling with respect to model
uncertainties, and propose a robust self-triggered sampling method. The
approach is compared with existing methods in terms of sampling
conservativeness and closed-loop system performance. The proposed method aims
at fulfilling the gap between the event and the self-triggered sampling
paradigms for what concerns robustness with respect to model uncertainties, and
it generalizes most of the existing self-triggered samplers implemented up to
now.
