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Data-Based Mechanistic Modelling (DBM) and control of mass and energy transfer in agricultural buildings

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Data-Based Mechanistic Modelling (DBM) and control of mass and energy transfer in agricultural buildings. / Price, Laura; Young, Peter C.; Berckmans, Daniel et al.
In: Annual Reviews in Control, Vol. 23, No. 1, 1999, p. 71-82.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

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Price L, Young PC, Berckmans D, Janssens K, Taylor CJ. Data-Based Mechanistic Modelling (DBM) and control of mass and energy transfer in agricultural buildings. Annual Reviews in Control. 1999;23(1):71-82. doi: 10.1016/S1367-5788(99)90063-9

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Price, Laura ; Young, Peter C. ; Berckmans, Daniel et al. / Data-Based Mechanistic Modelling (DBM) and control of mass and energy transfer in agricultural buildings. In: Annual Reviews in Control. 1999 ; Vol. 23, No. 1. pp. 71-82.

Bibtex

@article{72c0e01eea3d411fb3ac98897c0f4b36,
title = "Data-Based Mechanistic Modelling (DBM) and control of mass and energy transfer in agricultural buildings",
abstract = "This paper discusses the Data-Based Mechanistic (DBM) approach to modelling the micro-climate in agricultural buildings. Here, the imperfect mixing processes that dominate the system behaviour during forced ventilation are first modelled objectively, in purely data-based terms, by continuous-time transfer function relationships. In their equivalent differential equation form, however, these models can be interpreted in terms of the Active Mixing Volume (AMV) concept, developed previously at Lancaster in connection with pollution transport in rivers and soils and, latterly, in modelling the micro-climate of horticultural glasshouses. The data used in the initial stages of the research project, as described in the paper, have been obtained from a series of planned ventilation experiments carried out in a large instrumented chamber at Leuven. The overall objectives of this collaborative study are two-fold: first, to gain a better understanding of the mass and heat transfer dynamics in the chamber; and second, to develop models that can form the basis for the design of optimal Proportional-Integral-Plus, Linear Quadratic (PIP-LQ) climate control systems for livestock buildings of a kind used previously for controlling the micro-climate in horticultural glasshouses.",
keywords = "Data-based modelling, imperfect mixing, forced ventilation, micro-climate, heat and mass transfer, active mixing volume, control volume, optimal control",
author = "Laura Price and Young, {Peter C.} and Daniel Berckmans and Karl Janssens and Taylor, {C. James}",
year = "1999",
doi = "10.1016/S1367-5788(99)90063-9",
language = "English",
volume = "23",
pages = "71--82",
journal = "Annual Reviews in Control",
issn = "1367-5788",
publisher = "Elsevier Limited",
number = "1",

}

RIS

TY - JOUR

T1 - Data-Based Mechanistic Modelling (DBM) and control of mass and energy transfer in agricultural buildings

AU - Price, Laura

AU - Young, Peter C.

AU - Berckmans, Daniel

AU - Janssens, Karl

AU - Taylor, C. James

PY - 1999

Y1 - 1999

N2 - This paper discusses the Data-Based Mechanistic (DBM) approach to modelling the micro-climate in agricultural buildings. Here, the imperfect mixing processes that dominate the system behaviour during forced ventilation are first modelled objectively, in purely data-based terms, by continuous-time transfer function relationships. In their equivalent differential equation form, however, these models can be interpreted in terms of the Active Mixing Volume (AMV) concept, developed previously at Lancaster in connection with pollution transport in rivers and soils and, latterly, in modelling the micro-climate of horticultural glasshouses. The data used in the initial stages of the research project, as described in the paper, have been obtained from a series of planned ventilation experiments carried out in a large instrumented chamber at Leuven. The overall objectives of this collaborative study are two-fold: first, to gain a better understanding of the mass and heat transfer dynamics in the chamber; and second, to develop models that can form the basis for the design of optimal Proportional-Integral-Plus, Linear Quadratic (PIP-LQ) climate control systems for livestock buildings of a kind used previously for controlling the micro-climate in horticultural glasshouses.

AB - This paper discusses the Data-Based Mechanistic (DBM) approach to modelling the micro-climate in agricultural buildings. Here, the imperfect mixing processes that dominate the system behaviour during forced ventilation are first modelled objectively, in purely data-based terms, by continuous-time transfer function relationships. In their equivalent differential equation form, however, these models can be interpreted in terms of the Active Mixing Volume (AMV) concept, developed previously at Lancaster in connection with pollution transport in rivers and soils and, latterly, in modelling the micro-climate of horticultural glasshouses. The data used in the initial stages of the research project, as described in the paper, have been obtained from a series of planned ventilation experiments carried out in a large instrumented chamber at Leuven. The overall objectives of this collaborative study are two-fold: first, to gain a better understanding of the mass and heat transfer dynamics in the chamber; and second, to develop models that can form the basis for the design of optimal Proportional-Integral-Plus, Linear Quadratic (PIP-LQ) climate control systems for livestock buildings of a kind used previously for controlling the micro-climate in horticultural glasshouses.

KW - Data-based modelling

KW - imperfect mixing

KW - forced ventilation

KW - micro-climate

KW - heat and mass transfer

KW - active mixing volume

KW - control volume

KW - optimal control

U2 - 10.1016/S1367-5788(99)90063-9

DO - 10.1016/S1367-5788(99)90063-9

M3 - Journal article

VL - 23

SP - 71

EP - 82

JO - Annual Reviews in Control

JF - Annual Reviews in Control

SN - 1367-5788

IS - 1

ER -