Identification of a time-delayed process model using an overparameterisation method

John Roe

doi:10.21427/rxag-8x14

Identification of a time-delayed process model using an overparameterisation method

John Roe

Technological University Dublin

Research output: Contribution to conference › Paper › peer-review

Abstract

An extensive literature exists on the estimation of the model parameters of time-delayed processes. This paper briefly reviews the main overparameterisation methods for the Single-Input, Single Output (SISO) and Multi-Input, Multi-Output (MIMO) model parameter (and time delay) estimation problem. Subsequently, two algorithms, and their modifications, are discussed, and their performances are assessed in simulation. Results indicate that both the algorithms can suitably identify the model parameters, including the time delay. The third author has taught the method successfully to students taking advanced level control courses at DIT for a number of years; these experiences will be briefly reported. The paper also discusses the advantages and disadvantages of the overparameterisation approach.

Original language	English
DOIs	https://doi.org/10.21427/rxag-8x14
Publication status	Published - 2007
Event	China-Ireland International Conference on Information and Communications Technologies (CIICT) - DCU, Ireland Duration: 1 Aug 2007 → 31 Aug 2007

Conference

Conference	China-Ireland International Conference on Information and Communications Technologies (CIICT)
Country/Territory	Ireland
City	DCU
Period	1/08/07 → 31/08/07

Keywords

time-delayed processes
overparameterisation methods
SISO
MIMO
model parameter estimation
time delay
simulation
control courses
DIT
advantages
disadvantages

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10.21427/rxag-8x14Licence: CC BY-NC-SA

Cite this

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title = "Identification of a time-delayed process model using an overparameterisation method",

abstract = "An extensive literature exists on the estimation of the model parameters of time-delayed processes. This paper briefly reviews the main overparameterisation methods for the Single-Input, Single Output (SISO) and Multi-Input, Multi-Output (MIMO) model parameter (and time delay) estimation problem. Subsequently, two algorithms, and their modifications, are discussed, and their performances are assessed in simulation. Results indicate that both the algorithms can suitably identify the model parameters, including the time delay. The third author has taught the method successfully to students taking advanced level control courses at DIT for a number of years; these experiences will be briefly reported. The paper also discusses the advantages and disadvantages of the overparameterisation approach.",

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AB - An extensive literature exists on the estimation of the model parameters of time-delayed processes. This paper briefly reviews the main overparameterisation methods for the Single-Input, Single Output (SISO) and Multi-Input, Multi-Output (MIMO) model parameter (and time delay) estimation problem. Subsequently, two algorithms, and their modifications, are discussed, and their performances are assessed in simulation. Results indicate that both the algorithms can suitably identify the model parameters, including the time delay. The third author has taught the method successfully to students taking advanced level control courses at DIT for a number of years; these experiences will be briefly reported. The paper also discusses the advantages and disadvantages of the overparameterisation approach.

KW - time-delayed processes

KW - overparameterisation methods

KW - SISO

KW - MIMO

KW - model parameter estimation

KW - time delay

KW - simulation

KW - control courses

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KW - advantages

KW - disadvantages

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M3 - Paper

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Y2 - 1 August 2007 through 31 August 2007

ER -

Identification of a time-delayed process model using an overparameterisation method

Abstract

Conference

Keywords

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