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Authors: Daniel Beckmann ; Matthias Dagen and Tobias Ortmaier

Affiliation: Leibniz Universität Hannover, Germany

ISBN: 978-989-758-198-4

Keyword(s): Online Estimation, Kalman Filter, Discretization Methods, Mechanical System.

Related Ontology Subjects/Areas/Topics: Force and Tactile Sensors ; Informatics in Control, Automation and Robotics ; Signal Processing, Sensors, Systems Modeling and Control ; System Identification ; System Modeling

Abstract: This paper presents two symplectic discretization methods in the context of online parameter estimation for a nonlinear mechanical system. These symplectic approaches are compared to established discretization methods (e.g. Euler Forward and Runge Kutta) regarding accuracy and computational effort. In addition, the influence of the discretization method on the performance of an augmented Extended Kalman Filter (EKF) for parameter estimation is analyzed. The methods are compared with a nonlinear mechanical simulation model, based on a belt-drive system. The simulation shows improved accuracy using simplectic integrators in comparison to the conventional methods, with almost the same or lower computational cost. Parameter estimation based on the EKF in combination with the simplectic integration scheme leads to more accurate values.

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Paper citation in several formats:
Beckmann, D.; Dagen, M. and Ortmaier, T. (2016). Symplectic Discretization Methods for Parameter Estimation of a Nonlinear Mechanical System using an Extended Kalman Filter.In Proceedings of the 13th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO, ISBN 978-989-758-198-4, pages 327-334. DOI: 10.5220/0005973503270334

@conference{icinco16,
author={Daniel Beckmann. and Matthias Dagen. and Tobias Ortmaier.},
title={Symplectic Discretization Methods for Parameter Estimation of a Nonlinear Mechanical System using an Extended Kalman Filter},
booktitle={Proceedings of the 13th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,},
year={2016},
pages={327-334},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005973503270334},
isbn={978-989-758-198-4},
}

TY - CONF

JO - Proceedings of the 13th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,
TI - Symplectic Discretization Methods for Parameter Estimation of a Nonlinear Mechanical System using an Extended Kalman Filter
SN - 978-989-758-198-4
AU - Beckmann, D.
AU - Dagen, M.
AU - Ortmaier, T.
PY - 2016
SP - 327
EP - 334
DO - 10.5220/0005973503270334

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