Linear gaussian systems and event-based state estimation

Dawei Shi; Ling Shi; Tongwen Chen

doi:10.1007/978-3-319-26606-0_3

Linear gaussian systems and event-based state estimation

Dawei Shi^*, Ling Shi, Tongwen Chen

^*Corresponding author for this work

School of Automation

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

6 Citations (Scopus)

Abstract

Starting from this chapter, we look into the problems in event-based estimator design. Before moving onto the detailed discussions of the technical approaches utilized, we first introduce the basic components and ideas in event-based estimation in this chapter. In general, an event-based state estimation system (see Fig.3.1) is composed of four parts: the process to be estimated, the sensors, the event-triggering scheme and the estimator.

Original language	English
Title of host publication	Studies in Systems, Decision and Control
Publisher	Springer International Publishing
Pages	33-46
Number of pages	14
DOIs	https://doi.org/10.1007/978-3-319-26606-0_3
Publication status	Published - 2016

Publication series

Name	Studies in Systems, Decision and Control
Volume	41
ISSN (Print)	2198-4182
ISSN (Electronic)	2198-4190

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10.1007/978-3-319-26606-0_3

Cite this

Shi, D., Shi, L., & Chen, T. (2016). Linear gaussian systems and event-based state estimation. In Studies in Systems, Decision and Control (pp. 33-46). (Studies in Systems, Decision and Control; Vol. 41). Springer International Publishing. https://doi.org/10.1007/978-3-319-26606-0_3

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Linear gaussian systems and event-based state estimation

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