A Design Algorithm using External Perturbation to Improve Iterative Feedback Tuning Convergence

Publication: Research - peer-reviewJournal article – Annual report year: 2011

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A Design Algorithm using External Perturbation to Improve Iterative Feedback Tuning Convergence. / Huusom, Jakob Kjøbsted; Hjalmarsson, Håkan; Poulsen, Niels Kjølstad; Jørgensen, Sten Bay.

In: Automatica, Vol. 47, No. 12, 2011, p. 2665-2670.

Publication: Research - peer-reviewJournal article – Annual report year: 2011

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Huusom, Jakob Kjøbsted; Hjalmarsson, Håkan; Poulsen, Niels Kjølstad; Jørgensen, Sten Bay / A Design Algorithm using External Perturbation to Improve Iterative Feedback Tuning Convergence.

In: Automatica, Vol. 47, No. 12, 2011, p. 2665-2670.

Publication: Research - peer-reviewJournal article – Annual report year: 2011

Bibtex

@article{53649d9a442441998358c877f1cdbeee,
title = "A Design Algorithm using External Perturbation to Improve Iterative Feedback Tuning Convergence",
publisher = "Pergamon",
author = "Huusom, {Jakob Kjøbsted} and Håkan Hjalmarsson and Poulsen, {Niels Kjølstad} and Jørgensen, {Sten Bay}",
year = "2011",
doi = "10.1016/j.automatica.2011.05.029",
volume = "47",
number = "12",
pages = "2665--2670",
journal = "Automatica",
issn = "0005-1098",

}

RIS

TY - JOUR

T1 - A Design Algorithm using External Perturbation to Improve Iterative Feedback Tuning Convergence

A1 - Huusom,Jakob Kjøbsted

A1 - Hjalmarsson,Håkan

A1 - Poulsen,Niels Kjølstad

A1 - Jørgensen,Sten Bay

AU - Huusom,Jakob Kjøbsted

AU - Hjalmarsson,Håkan

AU - Poulsen,Niels Kjølstad

AU - Jørgensen,Sten Bay

PB - Pergamon

PY - 2011

Y1 - 2011

N2 - Iterative Feedback Tuning constitutes an attractive control loop tuning method for processes in the absence of process insight. It is a purely data driven approach for optimization of the loop performance. The standard formulation ensures an unbiased estimate of the loop performance cost function gradient, which is used in a search algorithm for minimizing the performance cost. A slow rate of convergence of the tuning method is often experienced when tuning for disturbance rejection. This is due to a poor signal to noise ratio in the process data. A method is proposed for increasing the data information content by introducing an optimal perturbation signal in the tuning algorithm. The theoretical analysis is supported by a simulation example where the proposed method is compared to an existing method for acceleration of the convergence by use of optimal prefilters.

AB - Iterative Feedback Tuning constitutes an attractive control loop tuning method for processes in the absence of process insight. It is a purely data driven approach for optimization of the loop performance. The standard formulation ensures an unbiased estimate of the loop performance cost function gradient, which is used in a search algorithm for minimizing the performance cost. A slow rate of convergence of the tuning method is often experienced when tuning for disturbance rejection. This is due to a poor signal to noise ratio in the process data. A method is proposed for increasing the data information content by introducing an optimal perturbation signal in the tuning algorithm. The theoretical analysis is supported by a simulation example where the proposed method is compared to an existing method for acceleration of the convergence by use of optimal prefilters.

KW - Controller tuning

KW - Direct tuning

KW - Iterative schemes

KW - Iterative Feedback Tuning

U2 - 10.1016/j.automatica.2011.05.029

DO - 10.1016/j.automatica.2011.05.029

JO - Automatica

JF - Automatica

SN - 0005-1098

IS - 12

VL - 47

SP - 2665

EP - 2670

ER -