Enhancing PI Tuning for Plant Commissioning Using Transfer Learning and Bayesian Optimization

Boulaid Boulkroune, Joachim Verhelst, Branimir Mrak, Bruno Depraetere, Joram Meskens, Pieter Bovijn

2025

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.

Paper Citation

in Harvard Style

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, SciTePress, pages 235-242. DOI: 10.5220/0013712600003982

in Bibtex Style

@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},
}

in EndNote Style

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
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