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.
Citations
-
0
CrossRef
-
0
Web of Science
-
0
Scopus
Authors (2)
Cite as
Full text
full text is not available in portal
Keywords
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
seen 162 times