Kalman Filtering of Discrete LPV Diabetes Mellitus Model for Control Purposes

György Eigner, Máté Siket, Levente Kovács

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

In this study we investigate the application of state estimation by using linear parameter varying (LPV) based extended Kalman filtering (EKF) concerning type 1 diabetes mellitus. We consider the widely used Cambridge model which has high complexity and several unfavorable properties from control engineering perspective. The applied model is transformed and scheduling variables are selected to keep the applicability of the selected complete LPV discretization method. We investigate two LPV models which are selected based on different benefits. Two EKFs are designed and the operation of them are compared to the original nonlinear model. According to the results both EKF can be applied despite their essential differences. Moreover, there is no significant deviation between their performance. Namely, both designed discrete LPV kind EKF estimated the states of the reference system with applicable error.

Original languageEnglish
Title of host publication18th IEEE International Symposium on Computational Intelligence and Informatics, CINTI 2018 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages119-124
Number of pages6
ISBN (Electronic)9781728111179
DOIs
Publication statusPublished - Nov 2018
Event18th IEEE International Symposium on Computational Intelligence and Informatics, CINTI 2018 - Budapest, Hungary
Duration: Nov 21 2018Nov 22 2018

Publication series

Name18th IEEE International Symposium on Computational Intelligence and Informatics, CINTI 2018 - Proceedings

Conference

Conference18th IEEE International Symposium on Computational Intelligence and Informatics, CINTI 2018
CountryHungary
CityBudapest
Period11/21/1811/22/18

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Keywords

  • Diabetes Mellitus
  • Discrete Linear Parameter Varying methodology
  • Extended Kalman Filter

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Information Systems
  • Information Systems and Management
  • Computational Mathematics
  • Modelling and Simulation

Cite this

Eigner, G., Siket, M., & Kovács, L. (2018). Kalman Filtering of Discrete LPV Diabetes Mellitus Model for Control Purposes. In 18th IEEE International Symposium on Computational Intelligence and Informatics, CINTI 2018 - Proceedings (pp. 119-124). [8928205] (18th IEEE International Symposium on Computational Intelligence and Informatics, CINTI 2018 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CINTI.2018.8928205