Details
| Original language | English |
|---|---|
| Title of host publication | Informatics in Control, Automation and Robotics - 13th International Conference, ICINCO 2016 |
| Editors | Dimitri Peaucelle, Kurosh Madani, Oleg Gusikhin |
| Publisher | Springer Verlag |
| Pages | 367-384 |
| Number of pages | 18 |
| ISBN (print) | 9783319550107 |
| Publication status | Published - 2018 |
| Event | 13th International Conference on Informatics in Control, Automation and Robotics, ICINCO 2016 - Lisbon, Portugal Duration: 29 Jul 2016 → 31 Jul 2016 |
Publication series
| Name | Lecture Notes in Electrical Engineering |
|---|---|
| Volume | 430 |
| ISSN (Print) | 1876-1100 |
| ISSN (electronic) | 1876-1119 |
Abstract
This paper presents two symplectic discretization methods in the context of online parameter estimation for nonlinear mechanical systems. The symplectic approaches are compared to established discretization methods (e.g. Euler Forward and Runge Kutta) regarding accuracy and computational effort. The methods are compared using two mechanical simulation models of a real belt-drive system: a nonlinear two-mass system with two degrees of freedom and a nonlinear three-mass system with three degrees of freedom. In addition, the influence of the discretization method on the performance of an augmented Extended Kalman Filter (EKF) estimating the parameter of the two-mass system is analyzed. The simulation shows improved accuracy of the calculated discrete-time solution using symplectic integrators in comparison to the conventional methods, with almost the same or lower computational cost. Additionally, the parameter estimation based on the EKF in combination with the symplectic integration scheme leads to more accurate values.
Keywords
- Discretization methods, Kalman filter, Mechanical system, Online estimation, Symplectic integrators
ASJC Scopus subject areas
- Engineering(all)
- Industrial and Manufacturing Engineering
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Informatics in Control, Automation and Robotics - 13th International Conference, ICINCO 2016. ed. / Dimitri Peaucelle; Kurosh Madani; Oleg Gusikhin. Springer Verlag, 2018. p. 367-384 (Lecture Notes in Electrical Engineering; Vol. 430).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - A comparison of discretization methods for parameter estimation of nonlinear mechanical systems using extended kalman filter
T2 - 13th International Conference on Informatics in Control, Automation and Robotics, ICINCO 2016
AU - Beckmann, Daniel
AU - Dagen, Matthias
AU - Ortmaier, Tobias
PY - 2018
Y1 - 2018
N2 - This paper presents two symplectic discretization methods in the context of online parameter estimation for nonlinear mechanical systems. The symplectic approaches are compared to established discretization methods (e.g. Euler Forward and Runge Kutta) regarding accuracy and computational effort. The methods are compared using two mechanical simulation models of a real belt-drive system: a nonlinear two-mass system with two degrees of freedom and a nonlinear three-mass system with three degrees of freedom. In addition, the influence of the discretization method on the performance of an augmented Extended Kalman Filter (EKF) estimating the parameter of the two-mass system is analyzed. The simulation shows improved accuracy of the calculated discrete-time solution using symplectic integrators in comparison to the conventional methods, with almost the same or lower computational cost. Additionally, the parameter estimation based on the EKF in combination with the symplectic integration scheme leads to more accurate values.
AB - This paper presents two symplectic discretization methods in the context of online parameter estimation for nonlinear mechanical systems. The symplectic approaches are compared to established discretization methods (e.g. Euler Forward and Runge Kutta) regarding accuracy and computational effort. The methods are compared using two mechanical simulation models of a real belt-drive system: a nonlinear two-mass system with two degrees of freedom and a nonlinear three-mass system with three degrees of freedom. In addition, the influence of the discretization method on the performance of an augmented Extended Kalman Filter (EKF) estimating the parameter of the two-mass system is analyzed. The simulation shows improved accuracy of the calculated discrete-time solution using symplectic integrators in comparison to the conventional methods, with almost the same or lower computational cost. Additionally, the parameter estimation based on the EKF in combination with the symplectic integration scheme leads to more accurate values.
KW - Discretization methods
KW - Kalman filter
KW - Mechanical system
KW - Online estimation
KW - Symplectic integrators
UR - http://www.scopus.com/inward/record.url?scp=85034263043&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-55011-4_18
DO - 10.1007/978-3-319-55011-4_18
M3 - Conference contribution
AN - SCOPUS:85034263043
SN - 9783319550107
T3 - Lecture Notes in Electrical Engineering
SP - 367
EP - 384
BT - Informatics in Control, Automation and Robotics - 13th International Conference, ICINCO 2016
A2 - Peaucelle, Dimitri
A2 - Madani, Kurosh
A2 - Gusikhin, Oleg
PB - Springer Verlag
Y2 - 29 July 2016 through 31 July 2016
ER -