TY - GEN
T1 - A Gaussian Sum Smoothing algorithm for Hammerstein-Wiener State-Space Systems
AU - Cedeno, Angel L.
AU - Carvajal, Rodrigo
AU - Aguero, Juan C.
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - In this paper, we develop a novel Bayesian smoothing method for obtaining the smoothed probability density functions of Hammerstein-Wiener state-space systems and the corresponding state estimation. The proposed smoother is designed using the two-filter approach, based on the Gaussian sum filtering algorithm and a backward filtering method. In this work, this backward filter is obtained using an approximation of the probability function of the non-linear output conditioned to the system state. Both the forward filter and the backward filter are used to obtain the Gaussian sum smoothing algorithm, which also includes the computation of the joint probability density function of the system state in two consecutive time instants. Numerical examples are presented to illustrate the benefits of our proposal.
AB - In this paper, we develop a novel Bayesian smoothing method for obtaining the smoothed probability density functions of Hammerstein-Wiener state-space systems and the corresponding state estimation. The proposed smoother is designed using the two-filter approach, based on the Gaussian sum filtering algorithm and a backward filtering method. In this work, this backward filter is obtained using an approximation of the probability function of the non-linear output conditioned to the system state. Both the forward filter and the backward filter are used to obtain the Gaussian sum smoothing algorithm, which also includes the computation of the joint probability density function of the system state in two consecutive time instants. Numerical examples are presented to illustrate the benefits of our proposal.
KW - Gaussian sum smoother
KW - Hammerstein-Wiener systems
KW - State estimation
KW - Two-filter formula
UR - http://www.scopus.com/inward/record.url?scp=85147095011&partnerID=8YFLogxK
U2 - 10.1109/ICA-ACCA56767.2022.10006105
DO - 10.1109/ICA-ACCA56767.2022.10006105
M3 - Conference contribution
AN - SCOPUS:85147095011
T3 - 2022 IEEE International Conference on Automation/25th Congress of the Chilean Association of Automatic Control: For the Development of Sustainable Agricultural Systems, ICA-ACCA 2022
BT - 2022 IEEE International Conference on Automation/25th Congress of the Chilean Association of Automatic Control
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2022 IEEE International Conference on Automation/25th Congress of the Chilean Association of Automatic Control, ICA-ACCA 2022
Y2 - 24 October 2022 through 28 October 2022
ER -
