Interval type-2 fuzzy neural network control for X-Y-Theta motion control stage using linear ultrasonic motors

Faa Jeng Lin, Syuan Yi Chen, Po Huan Chou, Po Huang Shieh

Research output: Contribution to journalArticle

31 Citations (Scopus)

Abstract

An interval type-2 fuzzy neural network (IT2FNN) control system is proposed to control the position of an X-Y-Theta (X-Y-θ) motion control stage using linear ultrasonic motors (LUSMs) to track various contours. The IT2FNN, which combines the merits of interval type-2 fuzzy logic system (FLS) and neural network, is developed to simplify the computation and to confront the uncertainties of the X-Y-θ motion control stage. Moreover, the parameter learning of the IT2FNN based on the supervised gradient descent method is performed on line. The experimental results show that the tracking performance of the IT2FNN is significantly improved compared to type-1 FNN.

Original languageEnglish
Pages (from-to)1138-1151
Number of pages14
JournalNeurocomputing
Volume72
Issue number4-6
DOIs
Publication statusPublished - 2009 Jan 1

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Keywords

  • Gradient descent method
  • Linear ultrasonic motors
  • Type-2 fuzzy logic system
  • Type-2 fuzzy neural network
  • X-Y-Theta motion control

ASJC Scopus subject areas

  • Computer Science Applications
  • Cognitive Neuroscience
  • Artificial Intelligence

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