loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Authors: Boulaid Boulkroune ; Joachim Verhelst ; Branimir Mrak ; Bruno Depraetere ; Joram Meskens and Pieter Bovijn

Affiliation: Flanders Make vzw, Oude Diestersebaan 133, 3920 Lommel, Belgium

Keyword(s): Controller Tuning, Transfer Learning, Bayesian Optimization, Thermal Plant.

Abstract: A novel approach for accelerating the auto-tuning of PI controllers during the commissioning phase is proposed in this study. This approach combines transfer learning and Bayesian optimization (BO) to minimize the number of iterations required to converge to the optimal solution. Transfer learning is employed to extract valuable information from available historical data derived from expert tuning of other equivalent process variants. In the absence of historical data, a simulation model can also be utilized to generate data from different model variants (e.g., changing the value of unknown parameters). In this study, a simulation model is used for generating historical data. The approach’s efficiency is demonstrated through its application to a thermal plant, achieving a significant reduction in the number of iterations required to reach the optimizer’s optimal solution.

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 216.73.216.118

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Boulkroune, B., Verhelst, J., Mrak, B., Depraetere, B., Meskens, J. and Bovijn, P. (2025). Enhancing PI Tuning for Plant Commissioning Using Transfer Learning and Bayesian Optimization. In Proceedings of the 22nd International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO; ISBN 978-989-758-770-2; ISSN 2184-2809, SciTePress, pages 235-242. DOI: 10.5220/0013712600003982

@conference{icinco25,
author={Boulaid Boulkroune and Joachim Verhelst and Branimir Mrak and Bruno Depraetere and Joram Meskens and Pieter Bovijn},
title={Enhancing PI Tuning for Plant Commissioning Using Transfer Learning and Bayesian Optimization},
booktitle={Proceedings of the 22nd International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO},
year={2025},
pages={235-242},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013712600003982},
isbn={978-989-758-770-2},
issn={2184-2809},
}

TY - CONF

JO - Proceedings of the 22nd International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO
TI - Enhancing PI Tuning for Plant Commissioning Using Transfer Learning and Bayesian Optimization
SN - 978-989-758-770-2
IS - 2184-2809
AU - Boulkroune, B.
AU - Verhelst, J.
AU - Mrak, B.
AU - Depraetere, B.
AU - Meskens, J.
AU - Bovijn, P.
PY - 2025
SP - 235
EP - 242
DO - 10.5220/0013712600003982
PB - SciTePress

- Science and Technology Publications, Lda.
RESOURCES

Proceedings

Papers

Authors

Ontology

CONTACTS

Science and Technology Publications, Lda
Avenida de S. Francisco Xavier, Lote 7 Cv. C,
2900-616 Setúbal, Portugal.

Phone: +351 265 520 185 (National fixed network call)
Fax: +351 265 520 186
Email: info@scitepress.org

EXTERNAL LINKS

PRIMORIS

INSTICC

SCITEVENTS

CROSSREF

COPE

PROCEEDINGS SUBMITTED FOR INDEXATION BY:

dblp

Ei Compendex

SCOPUS

Semantic Scholar

Google Scholar

Microsoft Academic