Artículo
Convergence and Accuracy Analysis for a Distributed Static State Estimator based on Gaussian Belief Propagation
Fecha de publicación:
11/2020
Editorial:
Institute of Electrical and Electronics Engineers
Revista:
IEEE Transactions on Automatic Control
ISSN:
0018-9286
Idioma:
Inglés
Tipo de recurso:
Artículo publicado
Clasificación temática:
Resumen
This paper focuses on the distributed static estimation problem and a Belief Propagation (BP) based estimation algorithm is proposed. We provide a complete analysis for convergence and accuracy of it. More precisely, we offer conditions under which the proposed distributed estimator is guaranteed to converge and we give concrete characterizations of its accuracy. Our results not only give a new algorithm with good performance but also provide a useful analysis framework to learn the properties of a distributed algorithm. It yields better theoretical understanding of the static distributed state estimator and may generate more applications in the future.
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Articulos(CIFASIS)
Articulos de CENTRO INT.FRANCO ARG.D/CS D/L/INF.Y SISTEM.
Articulos de CENTRO INT.FRANCO ARG.D/CS D/L/INF.Y SISTEM.
Citación
Marelli, Damian Edgardo; Sui, Tianju; Fu, Minyue; Sun, Ximing; Convergence and Accuracy Analysis for a Distributed Static State Estimator based on Gaussian Belief Propagation; Institute of Electrical and Electronics Engineers; IEEE Transactions on Automatic Control; 66; 10; 11-2020; 4785-4791
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