Conference paper
A Numerically Robust ESDIRK-Based Implementation of the Continuous-Discrete Extended Kalman Filter
Scientific Computing, Department of Informatics and Mathematical Modeling, Technical University of Denmark1
Department of Informatics and Mathematical Modeling, Technical University of Denmark2
Department of Chemical and Biochemical Engineering, Technical University of Denmark3
Mathematical Statistics, Department of Informatics and Mathematical Modeling, Technical University of Denmark4
We present a novel numerically robust and computationally efficient extended Kalman filter for state estimation in nonlinear continuous-discrete stochastic systems. The resulting differential equations for the mean-covariance evolution of the nonlinear stochastic continuous-discrete time systems are solved efficiently using an ESDIRK integrator with sensitivity analysis capabilities.
This ESDIRK integrator for the mean-covariance evolution is implemented as part of an extended Kalman filter and tested on a PDE system. For moderate to large sized systems, the ESDIRK based extended Kalman filter for nonlinear stochastic continuous-discrete time systems is more than two orders of magnitude faster than a conventional implementation.
This is of significance in nonlinear model predictive control applications, statistical process monitoring as well as grey-box modelling of systems described by stochastic differential equations.
Language: | English |
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Publisher: | IEEE |
Year: | 2007 |
Pages: | 2859-2866 |
Proceedings: | European Control Conference 2007 |
ISBN: | 3952417386 and 9783952417386 |
Types: | Conference paper |
DOI: | 10.23919/ECC.2007.7068978 |
ORCIDs: | Jørgensen, John Bagterp and Madsen, Henrik |