Event-Based State Estimation Using the Auxiliary Particle Filter

Forskningsoutput: Kapitel i bok/rapport/Conference proceedingKonferenspaper i proceeding

Abstract

Event-based sampling provides a way of lowering the resource utilization in sensing and communication applications. By sending a sample only when some triggering condition is fulfilled, we can ensure that the transmitted samples actually carry innovation. However, in an event-based system, the state estimation problem becomes complicated, as the information of not receiving a measurement must be taken into consideration. Recent research has examined the feasibility of using particle filters for solving the event-based state estimation problem. To the best of our knowledge, only the simple bootstrap particle filter has so far been considered in this setting. We argue that, as this filter does not fully utilize the current measurement, it is not well suited for state estimation in event-based systems.
We propose an extension to the auxiliary particle filter for systems with event-based measurements, in which certain existing techniques for finding an approximation of the fully adapted filter can easily be utilized. In a simulation study, we demonstrate that at new measurement events, the benefits of using the auxiliary particle filter increases when fewer measurements are being sent.

Detaljer

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Ämnesklassifikation (UKÄ) – OBLIGATORISK

  • Reglerteknik
Originalspråkengelska
Titel på värdpublikation2019 European Control Conference (ECC)
FörlagIEEE Press
ISBN (elektroniskt)978-3-907144-00-8
StatusPublished - 2019
PublikationskategoriForskning
Peer review utfördJa
Evenemang2019 European Control Conference - Napoli, Italien
Varaktighet: 2019 jun 252019 jun 28
http://ecc19.eu

Konferens

Konferens2019 European Control Conference
Förkortad titelECC19
LandItalien
OrtNapoli
Period2019/06/252019/06/28
Internetadress

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