Identification of compartmental models of diffusive systems by linear regression

Dirk Vries; Karel Keesman; Hans Zwart

Identification of compartmental models of diffusive systems by linear regression

Dirk Vries, Karel Keesman, Hans Zwart

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic

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Abstract

A linear regressive model structure and output predictor, both in algebraic form, are deduced from an LTI state space system with symmetric tridiagonal system matrix structure. In practice, systems with such a system matrix arise in modeling of distributed system configurations, and are known as compartmental systems. Two diffusion example cases are approximated by compartmental models and simulations of one case are worked out. Simulation results indicate that the method may be attractive for estimation, prediction and insight in compartmental systems, especially when physical knowledge is to be preserved.

Original language	English
Title of host publication	25th Benelux Meeting on Systems and Control, March 13-15, 2006, Heeze, The Netherlands
Subtitle of host publication	Book of Abstracts
Editors	Bram de Jager, Gjerrit Meinsma
Place of Publication	Eindhoven
Publisher	Technische Universiteit Eindhoven
Pages	17-17
Number of pages	1
ISBN (Print)	978-90-386-2558-4
Publication status	Published - 13 Mar 2006
Event	25th Benelux Meeting on Systems and Control 2006 - Heeze, Belgium Duration: 13 Mar 2006 → 15 Mar 2006 Conference number: 25

Conference

Conference	25th Benelux Meeting on Systems and Control 2006
Country	Belgium
City	Heeze
Period	13/03/06 → 15/03/06

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title = "Identification of compartmental models of diffusive systems by linear regression",

abstract = "A linear regressive model structure and output predictor, both in algebraic form, are deduced from an LTI state space system with symmetric tridiagonal system matrix structure. In practice, systems with such a system matrix arise in modeling of distributed system configurations, and are known as compartmental systems. Two diffusion example cases are approximated by compartmental models and simulations of one case are worked out. Simulation results indicate that the method may be attractive for estimation, prediction and insight in compartmental systems, especially when physical knowledge is to be preserved.",

author = "Dirk Vries and Karel Keesman and Hans Zwart",

year = "2006",

month = mar,

day = "13",

language = "English",

isbn = "978-90-386-2558-4",

pages = "17--17",

editor = "{de Jager}, Bram and Gjerrit Meinsma",

booktitle = "25th Benelux Meeting on Systems and Control, March 13-15, 2006, Heeze, The Netherlands",

publisher = "Technische Universiteit Eindhoven",

note = "25th Benelux Meeting on Systems and Control 2006 ; Conference date: 13-03-2006 Through 15-03-2006",

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Vries, D, Keesman, K & Zwart, H 2006, Identification of compartmental models of diffusive systems by linear regression. in B de Jager & G Meinsma (eds), 25th Benelux Meeting on Systems and Control, March 13-15, 2006, Heeze, The Netherlands: Book of Abstracts. Technische Universiteit Eindhoven, Eindhoven, pp. 17-17, 25th Benelux Meeting on Systems and Control 2006, Heeze, Belgium, 13/03/06.

Identification of compartmental models of diffusive systems by linear regression. / Vries, Dirk; Keesman, Karel; Zwart, Hans.

25th Benelux Meeting on Systems and Control, March 13-15, 2006, Heeze, The Netherlands: Book of Abstracts. ed. / Bram de Jager; Gjerrit Meinsma. Eindhoven : Technische Universiteit Eindhoven, 2006. p. 17-17.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic

TY - GEN

T1 - Identification of compartmental models of diffusive systems by linear regression

AU - Vries, Dirk

AU - Keesman, Karel

AU - Zwart, Hans

N1 - Conference code: 25

PY - 2006/3/13

Y1 - 2006/3/13

N2 - A linear regressive model structure and output predictor, both in algebraic form, are deduced from an LTI state space system with symmetric tridiagonal system matrix structure. In practice, systems with such a system matrix arise in modeling of distributed system configurations, and are known as compartmental systems. Two diffusion example cases are approximated by compartmental models and simulations of one case are worked out. Simulation results indicate that the method may be attractive for estimation, prediction and insight in compartmental systems, especially when physical knowledge is to be preserved.

AB - A linear regressive model structure and output predictor, both in algebraic form, are deduced from an LTI state space system with symmetric tridiagonal system matrix structure. In practice, systems with such a system matrix arise in modeling of distributed system configurations, and are known as compartmental systems. Two diffusion example cases are approximated by compartmental models and simulations of one case are worked out. Simulation results indicate that the method may be attractive for estimation, prediction and insight in compartmental systems, especially when physical knowledge is to be preserved.

M3 - Conference contribution

SN - 978-90-386-2558-4

SP - 17

EP - 17

BT - 25th Benelux Meeting on Systems and Control, March 13-15, 2006, Heeze, The Netherlands

A2 - de Jager, Bram

A2 - Meinsma, Gjerrit

PB - Technische Universiteit Eindhoven

CY - Eindhoven

T2 - 25th Benelux Meeting on Systems and Control 2006

Y2 - 13 March 2006 through 15 March 2006

ER -

Identification of compartmental models of diffusive systems by linear regression

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