Application of fuzzy reasoning and neural network to feed rate control of a machining robot

Fusaomi Nagata, Shohei Hayashi, Tomoya Nagatmi, Akimasa Otsuka, Keigo Watanabe

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

In the previous work, a machining robot based on an industrial robot was developed for foamed polystyrene materials. A robotic CAM system was incorporated in the robot to realize teachingless operation. In this paper, a fuzzy reasoning method processing radius of curvature is designed to skilfully regulate endmill's feed rate. The basic design of the machining robot using the fuzzy feed rate controller is presented for foamed polystyrene materials. Further, it is demonstrated that the mapping obtained by the fuzzy feed rate controller is well replaced by a multi-layered neural network.

Original languageEnglish
Pages (from-to)897-905
Number of pages9
JournalInternational Journal of Applied Electromagnetics and Mechanics
Volume52
Issue number3-4
DOIs
Publication statusPublished - 2016

Fingerprint

robots
machining
Machining
Polystyrenes
Robots
Neural networks
polystyrene
controllers
Controllers
Industrial robots
Computer aided manufacturing
computer aided manufacturing
Robotics
robotics
curvature
Processing
radii

Keywords

  • CAD/CAM
  • feed rate control
  • fuzzy control
  • Machining robot
  • neural networks

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Mechanics of Materials
  • Mechanical Engineering
  • Electrical and Electronic Engineering

Cite this

Application of fuzzy reasoning and neural network to feed rate control of a machining robot. / Nagata, Fusaomi; Hayashi, Shohei; Nagatmi, Tomoya; Otsuka, Akimasa; Watanabe, Keigo.

In: International Journal of Applied Electromagnetics and Mechanics, Vol. 52, No. 3-4, 2016, p. 897-905.

Research output: Contribution to journalArticle

Nagata, Fusaomi ; Hayashi, Shohei ; Nagatmi, Tomoya ; Otsuka, Akimasa ; Watanabe, Keigo. / Application of fuzzy reasoning and neural network to feed rate control of a machining robot. In: International Journal of Applied Electromagnetics and Mechanics. 2016 ; Vol. 52, No. 3-4. pp. 897-905.
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