@inproceedings{e18ca08a756d47b0a97a6c749b801667,
title = "Data-driven Control of Event-triggered Linear Systems",
abstract = "The present paper considers the data-driven control of unknown linear time-invariant discrete-time systems under an event-triggering transmission scheme. To this end, we begin by presenting a dynamic event-triggering scheme (ETS) based on periodic sampling, and a discrete-time looped-functional (DLF) approach, through which a model-based stability condition is derived. Combining the model-based condition with a recent data-based system representation, a data-driven stability criterion in the form of linear matrix inequalities (LMIs) is established, which offers a way of co-designing the ETS matrix and the controller using pre-collected noisy input-state data. Finally, numerical simulations showcase the efficacy of ETS in reducing data transmissions as well as of the proposed co-design methods.",
keywords = "and discrete-time systems, data-driven control, event-triggering scheme",
author = "Xin Wang and Jian Sun and Gang Wang",
note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 11th IEEE Data Driven Control and Learning Systems Conference, DDCLS 2022 ; Conference date: 03-08-2022 Through 05-08-2022",
year = "2022",
doi = "10.1109/DDCLS55054.2022.9858423",
language = "English",
series = "Proceedings of 2022 IEEE 11th Data Driven Control and Learning Systems Conference, DDCLS 2022",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1177--1182",
editor = "Mingxuan Sun and Zengqiang Chen",
booktitle = "Proceedings of 2022 IEEE 11th Data Driven Control and Learning Systems Conference, DDCLS 2022",
address = "United States",
}