English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Tools annual

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

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.

Symplectic Discretization Methods for Parameter Estimation of a Nonlinear Mechanical System using an Extended Kalman Filter