State Estimation for Distributed Systems with Stochastic and Set-membership Uncertainties

State estimation techniques for centralized, distributed, and decentralized systems are studied. An easy-to-implement state estimation concept is introduced that generalizes and combines basic principles of Kalman filter theory and ellipsoidal calculus. By means of this method, stochastic and set-me...

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Main Author: Noack, Benjamin (auth)
Format: Book Chapter
Published: KIT Scientific Publishing 2014
Subjects:
Online Access:Get Fullteks
DOAB: description of the publication
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005 20210212
020 |a KSP/1000036878 
020 |a 9783731501244 
024 7 |a 10.5445/KSP/1000036878  |c doi 
041 0 |a English 
042 |a dc 
100 1 |a Noack, Benjamin  |4 auth 
245 1 0 |a State Estimation for Distributed Systems with Stochastic and Set-membership Uncertainties 
260 |b KIT Scientific Publishing  |c 2014 
300 |a 1 electronic resource (XVIII, 257 p. p.) 
506 0 |a Open Access  |2 star  |f Unrestricted online access 
520 |a State estimation techniques for centralized, distributed, and decentralized systems are studied. An easy-to-implement state estimation concept is introduced that generalizes and combines basic principles of Kalman filter theory and ellipsoidal calculus. By means of this method, stochastic and set-membership uncertainties can be taken into consideration simultaneously. Different solutions for implementing these estimation algorithms in distributed networked systems are presented. 
540 |a Creative Commons  |f https://creativecommons.org/licenses/by-sa/4.0/  |2 cc  |4 https://creativecommons.org/licenses/by-sa/4.0/ 
546 |a English 
653 |a distributed estimation 
653 |a Kalman filter 
653 |a set-membership estimation 
653 |a Bayesian state estimation 
856 4 0 |a www.oapen.org  |u https://www.ksp.kit.edu/9783731501244  |7 0  |z Get Fullteks 
856 4 0 |a www.oapen.org  |u https://directory.doabooks.org/handle/20.500.12854/59976  |7 0  |z DOAB: description of the publication