A differential-algebraic multistate friction model

Xiaogang Xiong, Ryo Kikuuwe, Motoji Yamamoto

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

5 Citations (Scopus)

Abstract

Fidelity with friction properties and easiness of implementation are both important aspects for friction modeling. Some empirically motivated models can be implemented easily due to their simple expression and small number of parameters, but they cannot capture faithfully the main properties of friction. Some physically motivated models give close agreement with the friction properties, but they can be too complex for some applications. This paper proposes a differential-algebraic multistate friction model that possesses easiness of implementation and adjustment, a relatively small number of parameters and a compact formulation. Moreover, it captures all standard properties of well-established friction models.

Original languageEnglish
Title of host publicationSimulation, Modeling, and Programming for Autonomous Robots - Third International Conference, SIMPAR 2012, Proceedings
Pages77-88
Number of pages12
DOIs
Publication statusPublished - Nov 2 2012
Event3rd International Conference on Simulation, Modeling, and Programming for Autonomous Robots, SIMPAR 2012 - Tsukuba, Japan
Duration: Nov 5 2012Nov 8 2012

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7628 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other3rd International Conference on Simulation, Modeling, and Programming for Autonomous Robots, SIMPAR 2012
CountryJapan
CityTsukuba
Period11/5/1211/8/12

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All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Xiong, X., Kikuuwe, R., & Yamamoto, M. (2012). A differential-algebraic multistate friction model. In Simulation, Modeling, and Programming for Autonomous Robots - Third International Conference, SIMPAR 2012, Proceedings (pp. 77-88). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7628 LNAI). https://doi.org/10.1007/978-3-642-34327-8_10