A new version of this entry is available:
Loading...
Article
2025
On the structural analysis and optimal input design for joint state and parameter estimation
On the structural analysis and optimal input design for joint state and parameter estimation
Abstract (English)
This paper addresses the problem of joint state and parameter estimation for nonlinear affine-input systems with positive parameters including the design of a closed-loop optimal input adaptation to increase an identifiability measure for the system. The identifiability itself is considered in the context of structural observability of the system dynamics based on structural analysis of the system including the unknown parameters as additional states. In particular, the network graph-based interpretation of structural observability is employed at this point. This analysis motivates to include time derivatives of the measurements as additional system outputs to enhance the structural observability properties. For this purpose robust exact differentiation is considered, relying on the super-twisting algorithm to obtain finite time convergent estimates of these signals. Using the extended measurement signal, a continuous-discrete Extended Kalman filter is proposed that ensures strictly positive estimates for the parameters. Based on the estimates of states and parameters the input signal is determined using a moving horizon optimal predictive control that evaluates the condition number of the Fisher information matrix, thus maximizing the information content of the measurements with respect to the parameters. The proposed scheme extends and combines different previously discussed approaches from the literature and is evaluated by means of a thermal process example in simulation and experiment, showing high potential for similar system identification problems.
File is subject to an embargo until
This is a correction to:
A correction to this entry is available:
This is a new version of:
Other version
Notes
Publication license
Publication series
Published in
IEEE access, 13 (2025), 211944-211959.
https://doi.org/10.1109/ACCESS.2025.3636666.
ISSN: 2169-3536
New York : IEEE
Other version
Faculty
Institute
Examination date
Supervisor
Cite this publication
Lepsien, A., Kügler, P., & Schaum, A. (2025). On the structural analysis and optimal input Design for joint state and parameter estimation. IEEE access, 13. https://doi.org/10.1109/ACCESS.2025.3636666
Edition / version
Citation
DOI
ISSN
ISBN
Language
English
Publisher
Publisher place
Classification (DDC)
000 Computer science, information and general works
Original object
University bibliography
Standardized keywords (GND)
Sustainable Development Goals
BibTeX
@article{Lepsien2025,
url = {https://hohpublica.uni-hohenheim.de/handle/123456789/18761},
doi = {10.1109/ACCESS.2025.3636666},
author = {Lepsien, Arthur and Kügler, Philipp and Schaum, Alexander et al.},
title = {On the structural analysis and optimal input Design for joint state and parameter estimation},
journal = {IEEE access},
year = {2025},
volume = {13},
pages = {211944--211959},
}