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Authors: Vlad Muresan ; Mihail Abrudean ; Honoriu Valean ; Tiberiu Coloşi ; Mihaela-Ligia Unguresan ; Valentin Sita ; Iulia Clitan and Daniel Moga

Affiliation: Technical University of Cluj-Napoca, Romania

ISBN: 978-989-758-122-9

Keyword(s): Separation Column, 13C Isotope, Internal Model Control Strategy, Neural Networks, Distributed Parameter Process, Approximating Analytical Solution.

Related Ontology Subjects/Areas/Topics: Engineering Applications ; Industrial Automation and Robotics ; Industrial Engineering ; Informatics in Control, Automation and Robotics ; Intelligent Components for Control ; Intelligent Control Systems and Optimization ; Neural Networks Based Control Systems ; Robotics and Automation ; Signal Processing, Sensors, Systems Modeling and Control ; System Modeling ; Systems Modeling and Simulation

Abstract: The paper presents a solution for the 13C isotope concentration control inside and at the output of a separation column, solution based on the Internal Model Control strategy. The 13C isotope results from a chemical exchange process carbon dioxide – carbamate, which is a distributed parameter process. In order to model the mentioned process, an original form of the approximating analytical solution which describes the process work in transitory regime is determined. The evolution of the approximating solution depends both on time and on the position from the column height. The reference model of the fixed part of the control structure is implemented using neural networks, representing an original solution due to the fact that a neural model is determined for a distributed parameter process. The controller is, also, implemented using neural networks, its main parameter being adapted in relation to the transducer position change in the separation column. The advantages of using the prop osed concentration control strategy consist of: the possibility of controlling the value of the 13C isotope concentration in any point from the separation column height; the improvement of the system performance regarding the settling time; the possibility to reject the effect of the disturbances. (More)

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Paper citation in several formats:
Muresan, V.; Abrudean, M.; Valean, H.; Coloşi, T.; Unguresan, M.; Sita, V.; Clitan, I. and Moga, D. (2015). Neural Modeling and Control of a 13C Isotope Separation Process.In Proceedings of the 12th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO, ISBN 978-989-758-122-9, pages 254-263. DOI: 10.5220/0005549002540263

@conference{icinco15,
author={Vlad Muresan. and Mihail Abrudean. and Honoriu Valean. and Tiberiu Coloşi. and Mihaela{-}Ligia Unguresan. and Valentin Sita. and Iulia Clitan. and Daniel Moga.},
title={Neural Modeling and Control of a 13C Isotope Separation Process},
booktitle={Proceedings of the 12th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,},
year={2015},
pages={254-263},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005549002540263},
isbn={978-989-758-122-9},
}

TY - CONF

JO - Proceedings of the 12th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,
TI - Neural Modeling and Control of a 13C Isotope Separation Process
SN - 978-989-758-122-9
AU - Muresan, V.
AU - Abrudean, M.
AU - Valean, H.
AU - Coloşi, T.
AU - Unguresan, M.
AU - Sita, V.
AU - Clitan, I.
AU - Moga, D.
PY - 2015
SP - 254
EP - 263
DO - 10.5220/0005549002540263

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