Three-degree-of-freedom dynamic model based IT2RFNN control for gantry position stage

Po Huan Chou, Faa Jeng Lin, Chin Sheng Chen, Feng Chi Lee

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

Abstract

A three-degree-of-freedom (3-DOF) dynamic model based interval type-2 recurrent fuzzy neural network (IT2RFNN) control system is proposed in this study for a gantry position stage. To consider the effect of inter-axis mechanical coupling, a Lagrangian equation based 3-DOF dynamic model for gantry position stage is derived first. Then, to minimize the synchronous error and tracking error of the gantry position stage, the 3-DOF dynamic model based IT2RFNN control system is proposed. In this approach, the adaptive learning algorithms of the IT2RFNN on-line are derived from the Lyapunov stability theorem. Finally, some experimental results of optical inspection application are illustrated to show the validity of the proposed control approach.

Original languageEnglish
Title of host publicationLinear Drives for Industry Applications IX
Pages554-558
Number of pages5
DOIs
StatePublished - 2013
Event9th International Symposium on Linear Drives for Industry Applications, LDIA 2013 - Hangzhou, China
Duration: 7 Jul 201310 Jul 2013

Publication series

NameApplied Mechanics and Materials
Volume416-417
ISSN (Print)1660-9336
ISSN (Electronic)1662-7482

Conference

Conference9th International Symposium on Linear Drives for Industry Applications, LDIA 2013
Country/TerritoryChina
CityHangzhou
Period7/07/1310/07/13

Keywords

  • Gantry position stage
  • Interval type-2 fuzzy logic system
  • Lagrangian equation

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