Interval type-2 fuzzy neural network for ball and beam systems

Wei Shou Chan*, Chun Yi Lee, Chia Wen Chang, Yeong Hwa Chang

*Corresponding author for this work

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

6 Scopus citations

Abstract

An interval type-2 fuzzy neural network (IT2FNN) is developed for the position control of ball-and-beam systems to confront the noise. A T2FNN consists of a type-2 fuzzy linguistic process as the antecedent part and multi-layer neural network as the consequent part. The developed IT2FNN combines the merits of an interval type-2 fuzzy logic system and a neural network. Furthermore, the parameter-learning of the IT2FNN, which is based on the gradient decent method using adaptation law, is performed on line. Simulation results show that the dynamic behaviors of the proposed IT2FNN control system are more effective and robust with regard to uncertainties than the interval type-2 fuzzy logic control scheme.

Original languageEnglish
Title of host publication2010 International Conference on System Science and Engineering, ICSSE 2010
Pages315-320
Number of pages6
DOIs
StatePublished - 2010
Event2010 International Conference on System Science and Engineering, ICSSE 2010 - Taipei, Taiwan
Duration: 01 07 201003 07 2010

Publication series

Name2010 International Conference on System Science and Engineering, ICSSE 2010

Conference

Conference2010 International Conference on System Science and Engineering, ICSSE 2010
Country/TerritoryTaiwan
CityTaipei
Period01/07/1003/07/10

Keywords

  • Ball and beam system
  • Interval type-2 fuzzy neural network

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