Digital Self-tuning Control for Pressure Process

Gediminas Liaucius, Vytautas Kaminskas

2014

Abstract

Two digital control systems - Self-tuning PID (Proportional-Integral-Derivative) Control and Predictor-based self-tuning control with constraints - for the continuous-time pressure process control are presented in this paper. The digital self-tuning PID control with optimization of closed-loop parameters and sampling period is proposed. The multidimensional optimization problem of closed-loop parameters and sampling period is solved by subcomponent search method that enables dividing the problem to one-dimensional optimization problems. The golden section search is adjusted to solve those – one-dimensional - optimization problems. The predictor-based self-tuning control with constraints is adapted for both minimum-phase and nonminimum-phase process models. The control quality of pressure process of both control systems has been experimentally investigated. The results of experimental analysis demonstrate that the digital self-tuning PID control with optimization is more efficient as compared to predictive-based self-tuning control with constraints for pressure process.

Paper Citation

in Harvard Style

Liaucius G. and Kaminskas V. (2014). Digital Self-tuning Control for Pressure Process . In Proceedings of the 11th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO, ISBN 978-989-758-039-0, pages 612-619. DOI: 10.5220/0005012106120619

in Bibtex Style

@conference{icinco14,
author={Gediminas Liaucius and Vytautas Kaminskas},
title={Digital Self-tuning Control for Pressure Process},
booktitle={Proceedings of the 11th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,},
year={2014},
pages={612-619},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005012106120619},
isbn={978-989-758-039-0},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 11th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,
TI - Digital Self-tuning Control for Pressure Process
SN - 978-989-758-039-0
AU - Liaucius G.
AU - Kaminskas V.
PY - 2014
SP - 612
EP - 619
DO - 10.5220/0005012106120619