Direct Continuous Time System Identification of MISO Transfer Function Models applied to Type 1 Diabetes
(2011) 50th IEEE Conference on Decision and Control and European Control Conference, 2011 p.5176-5181- Abstract
- This paper shows an application of continuous-time system identification methods to Type 1 diabetes. First, a general MISO transfer function structure with individual nominator and denominator polynomials for each input is assumed and a parameter estimation procedure via an iterative prediction error method presented. Then, the proposed identification method is evaluated on a simple simulation example and finally applied on real-life data from Type 1 diabetes patients with the purpose of modeling blood glucose dynamics. To this aim, the method was extended to consider the time-varying nature of the system.
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/2543997
- author
- Kirchsteiger, Harald ; Pölzer, Stephan ; Johansson, Rolf LU ; Renard, Eric and del Re, Luigi
- organization
- publishing date
- 2011
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- host publication
- Proc. 50th IEEE Conference on Decision and Control and European Control Conference (CDC-ECC-2011)
- pages
- 6 pages
- conference name
- 50th IEEE Conference on Decision and Control and European Control Conference, 2011
- conference location
- Orlando, Florida, United States
- conference dates
- 2011-12-12 - 2011-12-15
- external identifiers
-
- scopus:84860681727
- project
- DIAdvisor
- language
- English
- LU publication?
- yes
- id
- 10134cb9-7757-408c-87f5-17a8ce53d5f2 (old id 2543997)
- date added to LUP
- 2016-04-04 14:08:28
- date last changed
- 2024-05-29 06:52:34
@inproceedings{10134cb9-7757-408c-87f5-17a8ce53d5f2, abstract = {{This paper shows an application of continuous-time system identification methods to Type 1 diabetes. First, a general MISO transfer function structure with individual nominator and denominator polynomials for each input is assumed and a parameter estimation procedure via an iterative prediction error method presented. Then, the proposed identification method is evaluated on a simple simulation example and finally applied on real-life data from Type 1 diabetes patients with the purpose of modeling blood glucose dynamics. To this aim, the method was extended to consider the time-varying nature of the system.}}, author = {{Kirchsteiger, Harald and Pölzer, Stephan and Johansson, Rolf and Renard, Eric and del Re, Luigi}}, booktitle = {{Proc. 50th IEEE Conference on Decision and Control and European Control Conference (CDC-ECC-2011)}}, language = {{eng}}, pages = {{5176--5181}}, title = {{Direct Continuous Time System Identification of MISO Transfer Function Models applied to Type 1 Diabetes}}, url = {{https://lup.lub.lu.se/search/files/62893699/2544008.pdf}}, year = {{2011}}, }