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Estimation of a Stochastic Burgers' Equation Using an Ensemble Kalman Filter

Abstract

In this work, we consider a difficult problem of state estimation of nonlinear stochastic partial differential equations (SPDE) based on uncertain measurements. The presented solution uses the method of lines (MoL), which allows us to discretize a stochastic partial differential equation in a spatial dimension and represent it as a system of coupled continuous-time ordinary stochastic differential equations (SDE). For such a system it is possible to use the standard estimation methods based on Kalman filtration. In this paper we propose using an ensemble Kalman filter (EnKF), which due to its characteristics can be successfully applied to problems with hundreds of state variables. Finally, we present the simulation results, which confirm the effectiveness of the presented approach.

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Details

Category:
Conference activity
Type:
publikacja w wydawnictwie zbiorowym recenzowanym (także w materiałach konferencyjnych)
Title of issue:
2018 23rd International Conference on Methods & Models in Automation & Robotics (MMAR) strony 736 - 740
Language:
English
Publication year:
2018
Bibliographic description:
Domżalski M., Kowalczuk Z.: Estimation of a Stochastic Burgers' Equation Using an Ensemble Kalman Filter// 2018 23rd International Conference on Methods & Models in Automation & Robotics (MMAR)/ : , 2018, s.736-740
DOI:
Digital Object Identifier (open in new tab) 10.1109/mmar.2018.8486020
Verified by:
Gdańsk University of Technology

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