@inproceedings{2991e7825bbc400081b9656da2dc166a,
title = "On the nonexistence of event-based triggers that preserve Gaussian state in presence of package-drop",
abstract = "State estimation is a core objective in cyber-physical systems. In the state estimation problem over linear systems, the Kalman filter is the standard solution. The filter is the format on which the solutions to subsequent estimation problems are based. Among these problems are the estimation problem in the presence of packet drops and estimation problem involving event-based triggers. We study in this paper both phenomena simultaneously. In an attempt to find the Kalman-like filter, which proves the Gaussianity of the state and offers a set of update equations, our paper shows that no such filter exists. More precisely, one cannot find an event-based trigger such that under possible packet drops, the state variable remains a Gaussian variable. This conclusion can be reasonably extended to a more general setting.",
keywords = "State estimation, event-based triggers, packet drops",
author = "Enoch Kung and Junfeng Wu and Dawei Shi and Ling Shi",
note = "Publisher Copyright: {\textcopyright} 2017 American Automatic Control Council (AACC).; 2017 American Control Conference, ACC 2017 ; Conference date: 24-05-2017 Through 26-05-2017",
year = "2017",
month = jun,
day = "29",
doi = "10.23919/ACC.2017.7963121",
language = "English",
series = "Proceedings of the American Control Conference",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1233--1237",
booktitle = "2017 American Control Conference, ACC 2017",
address = "United States",
}