- Conference Paper
In this work model identification of state-dependent transport coefficients in distributed systems is considered. In many cases it is difficult to formulate a suitable candidate model based on physical insight or prior knowledge. General parameterizations have therefore to be employed leading to a large number of unknown parameters. This may be prohibitive for distributed systems due to the computational cost of parameter estimation. An incremental model identification procedure is therefore employed here. This approach reflects the model development process itself and splits the identification into a sequence of inverse problems. Thereby, uncertainty in each step is minimized and computational cost is reduced substantially. The implementation presented here uses results from inverse problems theory and is applied to the estimation of a concentration dependent diffusion coefficient. Show more
Journal / seriesIFAC Proceedings Volumes
Pages / Article No.
Subjectidentification; regularization; distributed parameter systems; parameter estimation; discrimination
Organisational unit09696 - Bardow, André / Bardow, André
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