Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

    We have a manual that explains all the features 

Record number 427523
Title Physical parameter estimation in spatial heat transport models with an application to food storage
Author(s) Mourik, S. van; Vries, D.; Ploegaert, J.P.M.; Zwart, H.; Keesman, K.J.
Source Biosystems Engineering 112 (2012)1. - ISSN 1537-5110 - p. 14 - 21.
DOI https://doi.org/10.1016/j.biosystemseng.2012.01.011
Department(s) Biometris (WU MAT)
Systems and Control Group
Livestock Research
Biomass Refinery and Process Dynamics
PE&RC
WIMEK
Publication type Refereed Article in a scientific journal
Publication year 2012
Keyword(s) system-identification - bagged potatoes - bulk-storage - cold-storage - simulation - foodstuffs
Abstract Parameter estimation plays an important role in physical modelling, but can be problematic due to the complexity of spatiotemporal models that are used for analysis, control and design in industry. In this paper we aim to circumvent these problems by using a methodology that approximates a model, or a part of a model, by a first-order plus dead time (FOPDT) approximation, explicit in the physical parameters. The FOPDT model with its physical parameters can be calibrated and validated to experimental data via an Output Error identification. The methodology is illustrated by a model of a temperature-controlled food storage room using experimental data. The complex part of the model is reduced to an accurate first-order model that has predictive power with respect to physical parameter variations. Moreover, this methodology allows one to test model adjustments for phenomena that were not considered in the physical model, in a relatively easy way. (C) 2012 IAgrE. Published by Elsevier Ltd. All rights reserved.
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