State Estimation Methods for Continuous-Discrete Nonlinear Systems involving Stochastic Differential Equations

@article{Nielsen2022StateEM,
  title={State Estimation Methods for Continuous-Discrete Nonlinear Systems involving Stochastic Differential Equations},
  author={Marcus M. K. Nielsen and Tobias Kasper Skovborg Ritschel and Ib Christensen and Jess Dragheim and Jakob Kj{\o}bsted Huusom and Krist V. Gernaey and John Bagterp J{\o}rgensen},
  journal={ArXiv},
  year={2022},
  volume={abs/2205.02730}
}
—In this work, we present methods for state estima- tion in continuous-discrete nonlinear systems involving stochastic differential equations. We present the extended Kalman filter, the unscented Kalman filter, the ensemble Kalman filter, and a particle filter. We implement the state estimation methods in Matlab. We evaluate the performance of the methods on a simulation of the modified four-tank system. We implement the state estimation methods for non-stiff systems, i.e., using an explicit… 

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