A Novel Filtering Method for Hammerstein-Wiener State-Space Systems

Angel L. Cedeno, Rodrigo Carvajal, Juan C. Aguero

Resultado de la investigación: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

Resumen

In this paper, we develop a novel filtering algorithm for Hammerstein-Wiener State-Space Systems. The likelihood function of the noisy nonlinear output signal given the system state is approximated by a Gaussian-Legendre quadrature rule. This approximation produces an explicit model of this likelihood function with a Gaussian Sum structure. Based on the general Bayesian filtering framework, we develop a Gaussian Sum Filter algorithm to obtain the a posteriori probability density function of the state given the current and past nonlinear output. With the characterization of the a posteriori probability function, we can obtain the associated statistics of the state. Finally, we present numerical examples to illustrate the benefits of our proposal.

Idioma originalInglés
Título de la publicación alojada2021 IEEE CHILEAN Conference on Electrical, Electronics Engineering, Information and Communication Technologies, CHILECON 2021
EditorialInstitute of Electrical and Electronics Engineers Inc.
ISBN (versión digital)9781665408738
DOI
EstadoPublicada - 2021
Publicado de forma externa
Evento2021 IEEE CHILEAN Conference on Electrical, Electronics Engineering, Information and Communication Technologies, CHILECON 2021 - Virtual, Online, Chile
Duración: 6 dic. 20219 dic. 2021

Serie de la publicación

Nombre2021 IEEE CHILEAN Conference on Electrical, Electronics Engineering, Information and Communication Technologies, CHILECON 2021

Conferencia

Conferencia2021 IEEE CHILEAN Conference on Electrical, Electronics Engineering, Information and Communication Technologies, CHILECON 2021
País/TerritorioChile
CiudadVirtual, Online
Período6/12/219/12/21

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