A hybrid approach for the initialization of tracking simulation systems

Gerardo Santillan Martinez, Tommi Karhela, Hannu Niemistö, Ahti Rossi, Pang Cheng, Valeriy Vyatkin

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

7 Citations (Scopus)

Abstract

In the online and tracking simulation context, precise model initialization is highly important to ensure the quality of predictions made based on simulation. This paper presents a hybrid approach for the initialization of tracking simulation systems that combines different techniques and utilizes the persistent communication between model and process in order to initialize the simulation model. In the proposed approach, the model initialization is performed throughout different stages. A model is first fed with initial conditions that are close to the physical plant's state. Then, the model is run to the same state as the physical system using a process control system. Possible mass or energy errors in the state of the simulation model are corrected before the actual tracking process is started. This paper first introduces previously studied initialization techniques for online simulation systems. Then the proposed hybrid initialization method is elaborated. Finally, its implementation is demonstrated using a simple but representative process system.
Original languageEnglish
Title of host publicationEmerging Technologies & Factory Automation (ETFA), 2015 IEEE 20th Conference on
PublisherIEEE Institute of Electrical and Electronic Engineers
Pages1-8
ISBN (Electronic)978-1-4673-7929-8, 978-1-4673-7928-1
DOIs
Publication statusPublished - 26 Oct 2015
MoE publication typeA4 Article in a conference publication
EventIEEE 20th Conference on Emerging Technologies & Factory Automation - Luxembourg, France
Duration: 8 Sept 201511 Sept 2015
Conference number: 20

Conference

ConferenceIEEE 20th Conference on Emerging Technologies & Factory Automation
Abbreviated titleETFA
Country/TerritoryFrance
CityLuxembourg
Period8/09/1511/09/15

Keywords

  • adaption models
  • data models
  • water heating
  • integrated circuit modeling

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