Towards a systematic path for dynamic simulation to plant operation: OPC UA-enabled model adaptation method for tracking simulation

Gerardo Santillán Martínez; Tommi Karhela; Ruusu Reino; Tuomas Lackman; Valeriy Vyatkin

doi:10.1109/IECON.2017.8216952

Towards a systematic path for dynamic simulation to plant operation: OPC UA-enabled model adaptation method for tracking simulation

Gerardo Santillán Martínez, Tommi Karhela, Ruusu Reino, Tuomas Lackman, Valeriy Vyatkin

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

2 Citations (Scopus)

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Abstract

A tracking simulator is an online simulation system that utilizes dynamic parameter estimation for calibrating model parameters to achieve state synchronization with the process. It can be utilized as a plant-wide virtual sensors or as a predictive tool to provide production forecasts based on the current state of the plant. The appearance of industrial applications based on tracking simulators has been hindered by high development cost and time-consuming sustainability of simulation models. In order to overcome this, dynamic simulation models developed during the process design and engineering stages could be used for implementing industrial tracking simulators. However, before these models can be utilized online, they require going through a model adaptation procedure where their structure and parameters are updated. This paper presents a model adaptation method for the implementation of tracking simulators which utilizes OPC Unified Architecture to adapt simulation models developed during the engineering phases of the process plant and apply them at the operation and maintenance stages. In this work, the method is described, implemented and tested using a representative process.

Original language	English
Title of host publication	Proceedings of the 43rd Annual Conference of the IEEE Industrial Electronics Society, IECON 2017
Publisher	IEEE
Pages	5503-5508
Number of pages	6
ISBN (Electronic)	978-1-5386-1127-2
DOIs	https://doi.org/10.1109/IECON.2017.8216952
Publication status	Published - 2017
MoE publication type	A4 Article in a conference publication
Event	Annual Conference of the IEEE Industrial Electronics Society - Beijing, China Duration: 29 Oct 2017 → 1 Nov 2017 Conference number: 43 http://iecon2017.csp.escience.cn/

Publication series

Name	Proceedings of the Annual Conference of the IEEE Industrial Electronics Society
Publisher	IEEE
ISSN (Print)	1553-572X

Conference

Conference	Annual Conference of the IEEE Industrial Electronics Society
Abbreviated title	IECON
Country/Territory	China
City	Beijing
Period	29/10/2017 → 01/11/2017
Internet address	http://iecon2017.csp.escience.cn/

Keywords

process simulation
model adaptation
online simulation
OPC Unified Architecture
tracking simulation

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10.1109/IECON.2017.8216952

Martinez_etal_IECON_2017_5503
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Santillán Martínez, G., Karhela, T., Reino, R., Lackman, T., & Vyatkin, V. (2017). Towards a systematic path for dynamic simulation to plant operation: OPC UA-enabled model adaptation method for tracking simulation. In Proceedings of the 43rd Annual Conference of the IEEE Industrial Electronics Society, IECON 2017 (pp. 5503-5508). (Proceedings of the Annual Conference of the IEEE Industrial Electronics Society). IEEE. https://doi.org/10.1109/IECON.2017.8216952

Santillán Martínez, Gerardo ; Karhela, Tommi ; Reino, Ruusu et al. / Towards a systematic path for dynamic simulation to plant operation : OPC UA-enabled model adaptation method for tracking simulation. Proceedings of the 43rd Annual Conference of the IEEE Industrial Electronics Society, IECON 2017 . IEEE, 2017. pp. 5503-5508 (Proceedings of the Annual Conference of the IEEE Industrial Electronics Society).

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abstract = "A tracking simulator is an online simulation system that utilizes dynamic parameter estimation for calibrating model parameters to achieve state synchronization with the process. It can be utilized as a plant-wide virtual sensors or as a predictive tool to provide production forecasts based on the current state of the plant. The appearance of industrial applications based on tracking simulators has been hindered by high development cost and time-consuming sustainability of simulation models. In order to overcome this, dynamic simulation models developed during the process design and engineering stages could be used for implementing industrial tracking simulators. However, before these models can be utilized online, they require going through a model adaptation procedure where their structure and parameters are updated. This paper presents a model adaptation method for the implementation of tracking simulators which utilizes OPC Unified Architecture to adapt simulation models developed during the engineering phases of the process plant and apply them at the operation and maintenance stages. In this work, the method is described, implemented and tested using a representative process.",

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Santillán Martínez, G, Karhela, T, Reino, R, Lackman, T & Vyatkin, V 2017, Towards a systematic path for dynamic simulation to plant operation: OPC UA-enabled model adaptation method for tracking simulation. in Proceedings of the 43rd Annual Conference of the IEEE Industrial Electronics Society, IECON 2017 . Proceedings of the Annual Conference of the IEEE Industrial Electronics Society, IEEE, pp. 5503-5508, Annual Conference of the IEEE Industrial Electronics Society, Beijing, China, 29/10/2017. https://doi.org/10.1109/IECON.2017.8216952

Towards a systematic path for dynamic simulation to plant operation: OPC UA-enabled model adaptation method for tracking simulation. / Santillán Martínez, Gerardo; Karhela, Tommi; Reino, Ruusu et al.
Proceedings of the 43rd Annual Conference of the IEEE Industrial Electronics Society, IECON 2017 . IEEE, 2017. p. 5503-5508 (Proceedings of the Annual Conference of the IEEE Industrial Electronics Society).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

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AB - A tracking simulator is an online simulation system that utilizes dynamic parameter estimation for calibrating model parameters to achieve state synchronization with the process. It can be utilized as a plant-wide virtual sensors or as a predictive tool to provide production forecasts based on the current state of the plant. The appearance of industrial applications based on tracking simulators has been hindered by high development cost and time-consuming sustainability of simulation models. In order to overcome this, dynamic simulation models developed during the process design and engineering stages could be used for implementing industrial tracking simulators. However, before these models can be utilized online, they require going through a model adaptation procedure where their structure and parameters are updated. This paper presents a model adaptation method for the implementation of tracking simulators which utilizes OPC Unified Architecture to adapt simulation models developed during the engineering phases of the process plant and apply them at the operation and maintenance stages. In this work, the method is described, implemented and tested using a representative process.

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Santillán Martínez G, Karhela T, Reino R, Lackman T, Vyatkin V. Towards a systematic path for dynamic simulation to plant operation: OPC UA-enabled model adaptation method for tracking simulation. In Proceedings of the 43rd Annual Conference of the IEEE Industrial Electronics Society, IECON 2017 . IEEE. 2017. p. 5503-5508. (Proceedings of the Annual Conference of the IEEE Industrial Electronics Society). doi: 10.1109/IECON.2017.8216952

Towards a systematic path for dynamic simulation to plant operation: OPC UA-enabled model adaptation method for tracking simulation

Abstract

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Keywords

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