Hybrid grey box modelling of a pickling process
Document identifier: oai:dalea.du.se:1126
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10.1016/j.conengprac.2004.11.005Keyword: Engineering and Technology,
Electrical Engineering, Electronic Engineering, Information Engineering,
Teknik och teknologier,
Elektroteknik och elektronik,
Grey box modelling; nonlinear model; steel industry; Taylor series; identificationPublication year: 2005Relevant Sustainable Development Goals (SDGs):
The SDG label(s) above have been assigned by OSDG.aiAbstract: This paper deals with grey box modelling of an industrial process, in which known parts are modelled using a priori information and significant unknown parts are described as general continuous nonlinear functions. The modelling procedure follows a structured approach, which includes basic modelling, data acquisition, model calibration, hybrid expanded modelling, stochastic modelling and model appraisal. The general functions are approximated by means of the Taylor series including higher order terms, where the partial derivatives are estimated from measured data by minimising the maximum likelihood function. The Taylor series approach is used to keep the number of estimated parameters low in comparison with other nonlinear black box identification methods. The model is suitable for formulating algorithms to control the process, for example, a model predictive controller. The model can also be used to simulate various different production situations in order to improve the capacity of the total production line. Further, the relevant parts of the Taylor series can be used to explain in what way unknown process parts influence the behaviour of the process and give ideas for further investigation concerning the studied process
Authors
Björn Sohlberg
Högskolan Dalarna; Elektroteknik
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identifier: oai:dalea.du.se:1126
datestamp: 2021-04-15T13:13:34Z
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recordCreationDate: 2005-05-19
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http://urn.kb.se/resolve?urn=urn:nbn:se:du-1126
10.1016/j.conengprac.2004.11.005
titleInfo:
@attributes:
lang: eng
title: Hybrid grey box modelling of a pickling process
abstract: This paper deals with grey box modelling of an industrial process in which known parts are modelled using a priori information and significant unknown parts are described as general continuous nonlinear functions. The modelling procedure follows a structured approach which includes basic modelling data acquisition model calibration hybrid expanded modelling stochastic modelling and model appraisal. The general functions are approximated by means of the Taylor series including higher order terms where the partial derivatives are estimated from measured data by minimising the maximum likelihood function. The Taylor series approach is used to keep the number of estimated parameters low in comparison with other nonlinear black box identification methods. The model is suitable for formulating algorithms to control the process for example a model predictive controller. The model can also be used to simulate various different production situations in order to improve the capacity of the total production line. Further the relevant parts of the Taylor series can be used to explain in what way unknown process parts influence the behaviour of the process and give ideas for further investigation concerning the studied process
subject:
@attributes:
lang: eng
authority: uka.se
topic:
Engineering and Technology
Electrical Engineering Electronic Engineering Information Engineering
@attributes:
lang: swe
authority: uka.se
topic:
Teknik och teknologier
Elektroteknik och elektronik
@attributes:
lang: eng
topic: grey box modelling; nonlinear model; steel industry; Taylor series; identification
language:
languageTerm: eng
genre:
publication/journal-article
ref
note:
Published
1
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@attributes:
type: personal
authority: du
namePart:
Sohlberg
Björn
role:
roleTerm: aut
affiliation:
Högskolan Dalarna
Elektroteknik
nameIdentifier: bso
originInfo:
dateIssued: 2005
relatedItem:
@attributes:
type: host
titleInfo:
title: Control Engineering Practice
identifier:
0967-0661
1873-6939
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@attributes:
type: volume
number: 13
@attributes:
type: issue
number: 9
extent:
start: 1093
end: 1102
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form: print
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