A fuzzy neural network approach to model component behavior for virtual prototyping of hydraulic system

Wei Xiang, Sai Cheong Fok, Fook Fah Yap

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

1 Citation (Scopus)

Abstract

This paper proposes a fuzzy neural network (FNN) approach to model the behavior of a hydraulic component from input-output data. The approach uses an "effect" variable, which can be used to identify the significant inputs from the input-output data. The variations of the "effects" of the significant inputs are used to determine the number of fuzzy rules and the structure of the network. The proposed approach can be used to effectively map the input to output behavior of a hydraulic pressure control system. This is useful for virtual prototyping of fluid power systems.

Original languageEnglish
Title of host publicationProceedings of the 2001 ACM Symposium on Applied Computing, SAC 2001
PublisherAssociation for Computing Machinery
Pages482-483
Number of pages2
VolumePart F129805
ISBN (Print)1581132875, 9781581132878
DOIs
Publication statusPublished - Mar 1 2001
Externally publishedYes
Event2001 ACM Symposium on Applied Computing, SAC 2001 - Las Vegas, United States
Duration: Mar 11 2001Mar 14 2001

Publication series

NameProceedings of the ACM Symposium on Applied Computing

Conference

Conference2001 ACM Symposium on Applied Computing, SAC 2001
CountryUnited States
CityLas Vegas
Period3/11/013/14/01

Keywords

  • Fluid power system
  • Fuzzy neural network (FNN)

ASJC Scopus subject areas

  • Software

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