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Self-triggered control (STC) is a resource efficient approach to determinesampling instants for Networked Control Systems. At each sampling instant, anSTC mechanism determines not only the control inputs but also the next samplinginstant. In this article, an STC framework for perturbed nonlinear systems isproposed. In the framework, a dynamic variable is used in addition to currentstate information to determine the next sampling instant, rendering the STCmechanism dynamic. Using dynamic variables has proven to be powerful forincreasing sampling intervals for the closely related concept ofevent-triggered control, but has so far not been exploited for STC. Twovariants of the dynamic STC framework are presented. The first variant can beused without further knowledge on the disturbance and leads to guarantees oninput-to-state stability. The second variant exploits a known disturbance boundto determine sampling instants and guarantees asymptotic stability of a setcontaining the origin. In both cases, hybrid Lyapunov function techniques areused to derive the respective stability guarantees. Different choices for thedynamics of the dynamic variable, that lead to different particular STCmechanisms, are presented for both variants of the framework. The resultingdynamic STC mechanisms are illustrated with two numerical examples to emphasizetheir benefits in comparison to existing static STC approaches.

Robust dynamic self-triggered control for nonlinear systems using hybrid Lyapunov functions