Event-triggered Pulse Control with Model Learning (if Necessary)
Systems and Control
2019-03-20 v1
Abstract
In networked control systems, communication is a shared and therefore scarce resource. Event-triggered control (ETC) can achieve high performance control with a significantly reduced amount of samples compared to classical, periodic control schemes. However, ETC methods usually rely on the availability of an accurate dynamics model, which is oftentimes not readily available. In this paper, we propose a novel event-triggered pulse control strategy that learns dynamics models if necessary. In addition to adapting to changing dynamics, the method also represents a suitable replacement for the integral part typically used in periodic control.
Cite
@article{arxiv.1903.08046,
title = {Event-triggered Pulse Control with Model Learning (if Necessary)},
author = {Dominik Baumann and Friedrich Solowjow and Karl Henrik Johansson and Sebastian Trimpe},
journal= {arXiv preprint arXiv:1903.08046},
year = {2019}
}
Comments
Accepted final version to appear in: Proc. of the American Control Conference, 2019