Distributed Estimation on Sensor Networks With Measurement Uncertainties

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F21%3A00344562" target="_blank" >RIV/68407700:21230/21:00344562 - isvavai.cz</a>

Výsledek na webu

<a href="https://doi.org/10.1109/TCST.2020.3026815" target="_blank" >https://doi.org/10.1109/TCST.2020.3026815</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/TCST.2020.3026815" target="_blank" >10.1109/TCST.2020.3026815</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Distributed Estimation on Sensor Networks With Measurement Uncertainties

Popis výsledku v původním jazyce

This article brings distributed estimation for large-scale systems. The plant is considered affected by process disturbance, and measurements are corrupted by measurement noise. The proposed approach fuses measurements of differing reliability so that all nodes reach consensus on the plant's state estimate. This architecture is flexible to the addition of new nodes and, to a certain extent, robust to node or communication link failures. In spite of limited observability by each of the nodes, data fusion over the network allows each node to obtain the full estimate of the plant's state. Structured Lyapunov functions are used to prove the convergence of the estimator. Estimation error covariances are analyzed in detail. The proposed distributed observer design is validated by numerical simulations.

Název v anglickém jazyce

Distributed Estimation on Sensor Networks With Measurement Uncertainties

Popis výsledku anglicky

This article brings distributed estimation for large-scale systems. The plant is considered affected by process disturbance, and measurements are corrupted by measurement noise. The proposed approach fuses measurements of differing reliability so that all nodes reach consensus on the plant's state estimate. This architecture is flexible to the addition of new nodes and, to a certain extent, robust to node or communication link failures. In spite of limited observability by each of the nodes, data fusion over the network allows each node to obtain the full estimate of the plant's state. Structured Lyapunov functions are used to prove the convergence of the estimator. Estimation error covariances are analyzed in detail. The proposed distributed observer design is validated by numerical simulations.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

20205 - Automation and control systems

Projekt

<a href="/cs/project/GA19-18424S" target="_blank" >GA19-18424S: Distribuované řízení formací vozidel a síťových systémů</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2021

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

IEEE Transaction on Control Systems Technology

ISSN

1063-6536

e-ISSN

1558-0865

Svazek periodika

29

Číslo periodika v rámci svazku

5

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

15

Strana od-do

1997-2011

Kód UT WoS článku

000682140300012

EID výsledku v databázi Scopus

2-s2.0-85112777774