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Identification of Ill-conditioned plants — A benchmark problem

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The Modeling of Uncertainty in Control Systems

Part of the book series: Lecture Notes in Control and Information Sciences ((LNCIS,volume 192))

Abstract

This note provides a simple process example from chemical engineering which is proposed as a challenge problem for multivariable identification. The process considered is a simple heat-exchanger with two inputs and two outputs. It is strongly interactive and also ill-conditioned. A single slow pole, resulting from the interactions, is dominating all the individual open-loop responses. Attempting to identify a model based on fitting the individual transfer-matrix elements will usually result in a multivariable model which incorrectly has this dominant pole repeated. Such a model, although a reasonable model for the open-loop dynamics, yields a poor prediction of the process behavior under feedback control, in particular when considering partial control.

The note includes a description of the process, a file for generating open-loop “experimental” data and an example demonstrating that classical identification employing an ARMAX-type of model yields a model which is poor for feedback control studies of the process.

Financial support from the Royal Norwegian Council for Scientific and Industrial Research (NTNF) is greatfully acknowledged.

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Abbreviations

A:

heat transfer area (m 2)

c P :

heat capacity (kJCkg)

G(s):

process transfer-matrix for effect of inputs u

g ij (s):

transfer matrix element i,j

q C :

cold inlet flow (m 3/min)

q H :

hot inlet flow (m 3/min)

T C :

cold outlet temperature (°C)

T H :

hot outlet temperature (°C)

U:

heat transfer coefficient (kJ/m 2 °Cmin)

V C :

liquid volume cold side (m 3)

V H :

liquid volume hot side (m 3)

τ1 :

dominant (largest) process time-constant (min.)

τ2 :

smaller process time-constant (min.)

s:

setpoint change

References

  1. Jacobsen, E.W., P. Lundström and S. Skogestad, “Modelling and Identification for Robust Control of Ill-Conditioned Plants — A Distillation Case Study”, Proc. 1991 American Control Conference, Boston, 242–248, 1991.

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  2. Jacobsen, E. W. and S. Skogestad, “Inconsistencies in Dynamic Models for Ill-Conditioned Plants — with Application to Low-Order Models of Distillation Columns”, Submitted to Chem.Eng.Sci.., 1992

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  3. Kapoor, N. and T.J. McAvoy, “An Analytical Approach to Approximate Dynamic Modelling of Distillation Towers”, Ind.Eng.Chem.Res., 26, 2473–2482, 1987.

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  4. Ljung, L., System Identification Toolbox Version 3.0, MathWorks Inc., 1991.

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  5. Skogestad, S. and M. Morari, “Understanding the Dynamic Behavior of Distillation Columns”, Ind. & Eng. Chem. Res, 27, 10, 1848–1862, 1988.

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  6. Skogestad, S., M. Morari and J.C. Doyle, “Robust Control of Ill-Conditioned Plants: High-Purity Distillation”, IEEE Trans. Autom. Control, 33, 12, 1092–1105, 1988.

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Roy S. Smith PhD Mohammed Dahleh PhD

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© 1994 Springer-Verlag

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Jacobsen, E.W., Skogestad, S. (1994). Identification of Ill-conditioned plants — A benchmark problem. In: Smith, R.S., Dahleh, M. (eds) The Modeling of Uncertainty in Control Systems. Lecture Notes in Control and Information Sciences, vol 192. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0036269

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  • DOI: https://doi.org/10.1007/BFb0036269

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-19870-3

  • Online ISBN: 978-3-540-39327-6

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