Textile Sensor Surrogate Modeling Using Sparse Identification

  • Martin Steiger*
  • , Phillip Petz
  • , Stephan Schuler
  • *Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingsConference contributionpeer-review

Abstract

This paper addresses a possible surrogate model of a textile-based force sensor as introduced by Schuler et al., that is based on capacitance changes of conductive pads on the sensor surface caused by physical deformation. The proposed model is supposed to capture dynamic relationships between capacitance, force, and pull distance using a novel approach based on discrete Preisach hysteresis models in combination with Sparse Identifications of Non-linear Dynamics (SINDy), that is especially suitable for embedded systems applications.
Original languageEnglish
Title of host publicationComputer Aided Systems Theory - EUROCAST 2024 - 19th International Conference, 2024, Revised Selected Papers
EditorsAlexis Quesada-Arencibia, Michael Affenzeller, Roberto Moreno-Díaz
PublisherSpringer
Pages429-442
Number of pages14
ISBN (Print)9783031829512
DOIs
Publication statusPublished - 2025
Event19th International Conference on Computer Aided Systems Theory, EUROCAST 2024 - Las Palmas de Canaria, Spain
Duration: 25 Feb 20241 Mar 2024

Publication series

NameLecture Notes in Computer Science
Volume15172 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference19th International Conference on Computer Aided Systems Theory, EUROCAST 2024
Country/TerritorySpain
CityLas Palmas de Canaria
Period25.02.202401.03.2024

Keywords

  • Hysteresis Modeling
  • Soft Sensors
  • Sparse Identification

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