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

Abstract

Self-triggered control (STC) is a resource efficient approach to determine sampling instants for Networked Control Systems. At each sampling instant, an STC mechanism determines not only the control inputs but also the next sampling instant. In this article, an STC framework for perturbed nonlinear systems is proposed. In the framework, a dynamic variable is used in addition to current state information to determine the next sampling instant, rendering the STC mechanism dynamic. Using dynamic variables has proven to be powerful for increasing sampling intervals for the closely related concept of event-triggered control, but has so far not been exploited for STC. Two variants of the dynamic STC framework are presented. The first variant can be used without further knowledge on the disturbance and leads to guarantees on input-to-state stability. The second variant exploits a known disturbance bound to determine sampling instants and guarantees asymptotic stability of a set containing the origin. In both cases, hybrid Lyapunov function techniques are used to derive the respective stability guarantees. Different choices for the dynamics of the dynamic variable, that lead to different particular STC mechanisms, are presented for both variants of the framework. The resulting dynamic STC mechanisms are illustrated with two numerical examples to emphasize their benefits in comparison to existing static STC approaches.