A Comparison of Discretization Methods for Parameter Estimation of Nonlinear Mechanical Systems Using Extended Kalman Filter: Symplectic versus Classical Approaches

DOI10.1007/978-3-319-55011-4_18zbMath1427.93240OpenAlexW2766234887MaRDI QIDQ4972904

Matthias Dagen, Daniel Beckmann, Tobias Ortmaier

Publication date: 27 November 2019

Published in: Informatics in Control, Automation and Robotics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/978-3-319-55011-4_18

zbMATH Keywords

Kalman filtermechanical systemsymplectic integratorsdiscretization methodsonline estimation

Mathematics Subject Classification ID

Filtering in stochastic control theory (93E11) Nonlinear systems in control theory (93C10) Estimation and detection in stochastic control theory (93E10)

Related Items (2)

Particle swarm optimisation in nonlinear model predictive control; comprehensive simulation study for two selected problems ⋮ A Comparison of Discretization Methods for Parameter Estimation of Nonlinear Mechanical Systems Using Extended Kalman Filter: Symplectic versus Classical Approaches

Cites Work

• Practical grey-box process identification. Theory and applications
• Asymptotic behavior of the extended Kalman filter as a parameter estimator for linear systems
• A Comparison of Discretization Methods for Parameter Estimation of Nonlinear Mechanical Systems Using Extended Kalman Filter: Symplectic versus Classical Approaches
• Kalman Filtering
• Geometric Numerical Integration

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