|
|
Calibration of physical models with process data using FIR filtering |
|---|---|
| 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: |
AbstractAutomatic 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. see all
|
| 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). |
| EU Grant Number: |
(870130) COGNITWIN - COGNITIVE PLANTS THROUGH PROACTIVE SELF-LEARNING HYBRID DIGITAL TWINS |
| Copyright information: |
© 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |