Design of a Self-tuning Predictive PI Controller for Delay Systems based on the Augmented Output

Yoichiro Ashida, Shin Wakitani, Toru Yamamoto

2019

Abstract

This paper proposes an online type control parameter tuning method for a predictive PI controller. Predictive PI controller is based on a PI controller with a Smith predictor, and it is effective for a controlled object with large dead-time. Control performance of the predictive PI controller strongly depends on control parameters. Recently, some data-driven controller tuning methods have been proposed. The methods directly calculate suitable parameters from one or some sets of operating data. In addition, almost controlled processes are time-variant. In this paper, a data-driven self-tuning predictive PI controller is proposed. The effectiveness of the proposed scheme is evaluated by a simulation example.

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Paper Citation


in Harvard Style

Ashida Y., Wakitani S. and Yamamoto T. (2019). Design of a Self-tuning Predictive PI Controller for Delay Systems based on the Augmented Output.In Proceedings of the 16th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO, ISBN 978-989-758-380-3, pages 672-679. DOI: 10.5220/0007919306720679


in Bibtex Style

@conference{icinco19,
author={Yoichiro Ashida and Shin Wakitani and Toru Yamamoto},
title={Design of a Self-tuning Predictive PI Controller for Delay Systems based on the Augmented Output},
booktitle={Proceedings of the 16th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,},
year={2019},
pages={672-679},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007919306720679},
isbn={978-989-758-380-3},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 16th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,
TI - Design of a Self-tuning Predictive PI Controller for Delay Systems based on the Augmented Output
SN - 978-989-758-380-3
AU - Ashida Y.
AU - Wakitani S.
AU - Yamamoto T.
PY - 2019
SP - 672
EP - 679
DO - 10.5220/0007919306720679