Linear Switching System Identification Applied to Blast Furnace Data

Amir H. Shirdel, Kaj-Mikael Björk, Markus Holopainen, Christer Carlsson, Hannu T. Toivonen

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

1 Citation (Scopus)

Abstract

Switching systems are dynamical systems which can switch between a number of modes characterized by different dynamical behaviors. Several approaches have recently been presented for experimental identification of switching system, whereas studies on real-world applications have been scarce. This paper is focused on applying switching system identification to a blast furnace process. Specifically, the possibility of replacing nonlinear complex system models with a number of simple linear models is investigated. Identification of switching systems consists of identifying both the individual dynamical behavior of model which describes the system in the various modes, as well as the time instants when the mode changes have occurred. In this contribution a switching system identification method based on sparse optimization is used to construct linear switching dynamic models to describe the nonlinear system. The results obtained for blast furnace data are compared with a nonlinear model u sing Artificial Neural Fuzzy Inference System (ANFIS).
Original languageEnglish
Title of host publicationProceedings of the 11th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO, 2014, Vienna, Austria
Number of pages6
Volume1
PublisherSCITEPRESS Science And Technology Publications
Publication date2014
Pages643-648
ISBN (Print)978-989-758-039-0
DOIs
Publication statusPublished - 2014
MoE publication typeA4 Article in conference proceedings

Keywords

  • 512 Business and Management
  • System Identification
  • Linear Switching System
  • Blast Furnace
  • ANFIS
  • Nonlinear System
  • Sparse Optimization

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  • Cite this

    Shirdel, A. H., Björk, K-M., Holopainen, M., Carlsson, C., & Toivonen, H. T. (2014). Linear Switching System Identification Applied to Blast Furnace Data. In Proceedings of the 11th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO, 2014, Vienna, Austria (Vol. 1, pp. 643-648). SCITEPRESS Science And Technology Publications. https://doi.org/10.5220/0005022806430648