Control-relevant curvefitting for plant-friendly multivariable system identification

Hyunjin Lee; Daniel Rivera

Control-relevant curvefitting for plant-friendly multivariable system identification

Hyunjin Lee
, Daniel Rivera

Chemical Engineering

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

4 Scopus citations

Abstract

A control-relevant parameter estimation algorithm is developed in this paper for curvefitting Empirical Transfer Function Estimates (ETFEs) with orthogonal (i.e., zippered) frequency grids to discrete-time parametric Matrix Fraction Description models. Such ETFEs arise from DFT analysis of identification data generated from constrained, plant-friendly multisine inputs as developed by the authors' previous work. This curvefitter minimizes model estimation error using pre/post frequency-dependent weighting matrices as functions of the closed-loop dynamics. The control-relevant multivariable parameter estimation procedure is illustrated with an example case study based on the Shell Heavy Oil Fractionator problem.

Original language	English (US)
Title of host publication	Proceedings of the American Control Conference
Pages	1431-1436
Number of pages	6
Volume	2
State	Published - 2005
Event	2005 American Control Conference, ACC - Portland, OR, United States Duration: Jun 8 2005 → Jun 10 2005

Other

Other	2005 American Control Conference, ACC
Country/Territory	United States
City	Portland, OR
Period	6/8/05 → 6/10/05

ASJC Scopus subject areas

Control and Systems Engineering

Cite this

@inproceedings{4b612c985cec4ef48b794b94555f6d8d,

title = "Control-relevant curvefitting for plant-friendly multivariable system identification",

abstract = "A control-relevant parameter estimation algorithm is developed in this paper for curvefitting Empirical Transfer Function Estimates (ETFEs) with orthogonal (i.e., zippered) frequency grids to discrete-time parametric Matrix Fraction Description models. Such ETFEs arise from DFT analysis of identification data generated from constrained, plant-friendly multisine inputs as developed by the authors' previous work. This curvefitter minimizes model estimation error using pre/post frequency-dependent weighting matrices as functions of the closed-loop dynamics. The control-relevant multivariable parameter estimation procedure is illustrated with an example case study based on the Shell Heavy Oil Fractionator problem.",

author = "Hyunjin Lee and Daniel Rivera",

year = "2005",

language = "English (US)",

volume = "2",

pages = "1431--1436",

booktitle = "Proceedings of the American Control Conference",

note = "2005 American Control Conference, ACC ; Conference date: 08-06-2005 Through 10-06-2005",

}

TY - GEN

T1 - Control-relevant curvefitting for plant-friendly multivariable system identification

AU - Lee, Hyunjin

AU - Rivera, Daniel

PY - 2005

Y1 - 2005

N2 - A control-relevant parameter estimation algorithm is developed in this paper for curvefitting Empirical Transfer Function Estimates (ETFEs) with orthogonal (i.e., zippered) frequency grids to discrete-time parametric Matrix Fraction Description models. Such ETFEs arise from DFT analysis of identification data generated from constrained, plant-friendly multisine inputs as developed by the authors' previous work. This curvefitter minimizes model estimation error using pre/post frequency-dependent weighting matrices as functions of the closed-loop dynamics. The control-relevant multivariable parameter estimation procedure is illustrated with an example case study based on the Shell Heavy Oil Fractionator problem.

AB - A control-relevant parameter estimation algorithm is developed in this paper for curvefitting Empirical Transfer Function Estimates (ETFEs) with orthogonal (i.e., zippered) frequency grids to discrete-time parametric Matrix Fraction Description models. Such ETFEs arise from DFT analysis of identification data generated from constrained, plant-friendly multisine inputs as developed by the authors' previous work. This curvefitter minimizes model estimation error using pre/post frequency-dependent weighting matrices as functions of the closed-loop dynamics. The control-relevant multivariable parameter estimation procedure is illustrated with an example case study based on the Shell Heavy Oil Fractionator problem.

UR - https://www.scopus.com/pages/publications/23944458605

UR - https://www.scopus.com/pages/publications/23944458605#tab=citedBy

M3 - Conference contribution

AN - SCOPUS:23944458605

VL - 2

SP - 1431

EP - 1436

BT - Proceedings of the American Control Conference

T2 - 2005 American Control Conference, ACC

Y2 - 8 June 2005 through 10 June 2005

ER -

Control-relevant curvefitting for plant-friendly multivariable system identification

Abstract

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ASJC Scopus subject areas

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