An Eigenfunction Approach to Parameter Estimation for 1D Diffusion Problems

Conference contribution
(Conference Contribution)


Publication Details

Author(s): Schäfer M, Ruderer A, Rabenstein R
Publication year: 2019
Conference Proceedings Title: Proceedings of the 18th European Control Conference
Pages range: 3786 - 3789
Language: English


Abstract

The behavior of a distributed parameter system can be represented by an expansion into eigenfunctions. It allows to calculate the output signal in dependence on the parameters of the system. This contribution considers the inverse problem: Estimate the system parameters from noisy measurements of the output. To this end, an eigenfunction expansion serves to establish a state-space description of the distributed parameter system. The corresponding state-space matrices define an extended Kalman filter to perform estimation and tracking of parameter values. This approach is shown here for a diffusion problem in one spatial dimension. The value of the diffusion parameter is estimated from a simulated particle concentration under varying conditions. Problems of this kind arises for example in the emerging field of molecular communications.


FAU Authors / FAU Editors

Rabenstein, Rudolf Prof. Dr.
Lehrstuhl für Multimediakommunikation und Signalverarbeitung
Schäfer, Maximilian
Lehrstuhl für Multimediakommunikation und Signalverarbeitung


How to cite

APA:
Schäfer, M., Ruderer, A., & Rabenstein, R. (2019). An Eigenfunction Approach to Parameter Estimation for 1D Diffusion Problems. In Proceedings of the 18th European Control Conference (pp. 3786 - 3789). Neapel, IT.

MLA:
Schäfer, Maximilian, Alexander Ruderer, and Rudolf Rabenstein. "An Eigenfunction Approach to Parameter Estimation for 1D Diffusion Problems." Proceedings of the European Control Conference (ECC 19), Neapel 2019. 3786 - 3789.

BibTeX: 

Last updated on 2019-01-07 at 17:08