Dynamic self-triggered control for nonlinear systems based on hybrid Lyapunov functions

TL;DR

This paper introduces a dynamic self-triggered control mechanism for nonlinear systems that uses a hybrid Lyapunov function and a dynamic variable to significantly increase sampling intervals, improving efficiency over static methods.

Contribution

It proposes a novel dynamic STC mechanism utilizing a dynamic variable based on Lyapunov function values, filling a gap in existing control strategies.

Findings

Sampling intervals are significantly larger than static STC methods.

The mechanism guarantees an average decrease of the Lyapunov function.

Numerical example demonstrates improved performance.

Abstract

Self-triggered control (STC) is a well-established technique to reduce the amount of samples for sampled-data systems, and is hence particularly useful for Networked Control Systems. At each sampling instant, an STC mechanism determines not only an updated control input but also when the next sample should be taken. In this paper, a dynamic STC mechanism for nonlinear systems is proposed. The mechanism incorporates a dynamic variable for determining the next sampling instant. Such a dynamic variable for the trigger decision has been proven to be a powerful tool for increasing sampling intervals in the closely related concept of event-triggered control, but was so far not exploited for STC. This gap is closed in this paper. For the proposed mechanism, the dynamic variable is chosen to be the filtered values of the Lyapunov function at past sampling instants. The next sampling instant is, based on the dynamic variable and on hybrid Lyapunov function techniques, chosen such that an average decrease of the Lyapunov function is ensured. The proposed mechanism is illustrated with a numerical example from the literature. For this example, the obtained sampling intervals are significantly larger than for existing static STC mechanisms. This paper is the accepted version of [1], containing also proofs of the main results.