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

doi:10.3233/JAE-162217

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

School of Engineering

Research output: Contribution to journal › Article › peer-review

3 Citations (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 language	English
Pages (from-to)	897-905
Number of pages	9
Journal	International Journal of Applied Electromagnetics and Mechanics
Volume	52
Issue number	3-4
DOIs	https://doi.org/10.3233/JAE-162217
Publication status	Published - 2016

Keywords

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

ASJC Scopus subject areas

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

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10.3233/JAE-162217

Cite this

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AU - Hayashi, Shohei

AU - Nagatmi, Tomoya

AU - Otsuka, Akimasa

AU - Watanabe, Keigo

PY - 2016

Y1 - 2016

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AB - 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.

KW - CAD/CAM

KW - Machining robot

KW - feed rate control

KW - fuzzy control

KW - neural networks

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

Abstract

Keywords

ASJC Scopus subject areas

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