University of Oulu

E. Ikonen and I. Selek, "Calibration of Physical Models with Process Data using FIR Filtering," 2020 Australian and New Zealand Control Conference (ANZCC), Gold Coast, Australia, 2020, pp. 143-148, doi: 10.1109/ANZCC50923.2020.9318340

Calibration of physical models with process data using FIR filtering

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Author: Ikonen, Enso1; Selek, István1
Organizations: 1Intelligent Machines and Systems, University of Oulu, FIN-90014 Oulun yliopisto, Finland
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 0.1 MB)
Persistent link: http://urn.fi/urn:nbn:fi-fe202102094090
Language: English
Published: Institute of Electrical and Electronics Engineers, 2020
Publish Date: 2021-02-09
Description:

Abstract

Automatic calibration of physical plant models in the context of monitoring and control of industrial processes is considered. A structure integrating a physical model and estimated FIR filters is proposed. In addition, a finite state FIR structure is proposed to complement the calibrated physical model with a data-driven mapping. The approach is illustrated in simulations using the van der Vusse CSTR benchmark.

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ISBN: 978-1-7281-9992-4
ISBN Print: 978-1-7281-9991-7
Pages: 143 - 148
DOI: 10.1109/ANZCC50923.2020.9318340
OADOI: https://oadoi.org/10.1109/ANZCC50923.2020.9318340
Host publication: 2020 Australian & New Zealand Control Conference (ANZCC), proceedings
Conference: Australian & New Zealand Control Conference
Type of Publication: A4 Article in conference proceedings
Field of Science: 213 Electronic, automation and communications engineering, electronics
Subjects:
Funding: The work in this paper was partly funded by the H2020 project COGNITWIN (grant number 870130).
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