Control of human arm movement in machine-human cooperative welding process

Yu Kang Liu; Yu Ming Zhang

doi:10.1016/j.conengprac.2014.08.003

Control of human arm movement in machine-human cooperative welding process

Yu Kang Liu, Yu Ming Zhang

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

30 Scopus citations

Abstract

This paper studies accurate control of human arm movement in machine-human cooperative control of GTAW process. An innovative teleoperated virtualized welding platform is utilized to conduct dynamic experiments to correlate the human welder arm movement with the visual signal input. An adaptive ANFIS model is proposed to model the intrinsic nonlinear and time-varying characteristic of the human welder response. A model based predictive control algorithm is then proposed and an analytical solution is derived. Human control experimental results verify that the proposed controller is able to track varying set-points and is robust under measurement and input disturbances.

Original language	English
Pages (from-to)	161-171
Number of pages	11
Journal	Control Engineering Practice
Volume	32
DOIs	https://doi.org/10.1016/j.conengprac.2014.08.003
State	Published - Nov 1 2014

Bibliographical note

Funding Information:
This work is funded by the National Science Foundation under Grant IIS-1208420 . The authors thank the assistance from Mr. Ning Huang on the experiments.

Publisher Copyright:
© 2014 Elsevier Ltd.

Keywords

ANFIS
GTAW
Machine-human cooperative control
Model-based predictive control
Virtualized welding

ASJC Scopus subject areas

Control and Systems Engineering
Computer Science Applications
Electrical and Electronic Engineering
Applied Mathematics

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10.1016/j.conengprac.2014.08.003

Cite this

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title = "Control of human arm movement in machine-human cooperative welding process",

abstract = "This paper studies accurate control of human arm movement in machine-human cooperative control of GTAW process. An innovative teleoperated virtualized welding platform is utilized to conduct dynamic experiments to correlate the human welder arm movement with the visual signal input. An adaptive ANFIS model is proposed to model the intrinsic nonlinear and time-varying characteristic of the human welder response. A model based predictive control algorithm is then proposed and an analytical solution is derived. Human control experimental results verify that the proposed controller is able to track varying set-points and is robust under measurement and input disturbances.",

keywords = "ANFIS, GTAW, Machine-human cooperative control, Model-based predictive control, Virtualized welding",

author = "Liu, {Yu Kang} and Zhang, {Yu Ming}",

note = "Funding Information: This work is funded by the National Science Foundation under Grant IIS-1208420 . The authors thank the assistance from Mr. Ning Huang on the experiments. Publisher Copyright: {\textcopyright} 2014 Elsevier Ltd.",

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AU - Zhang, Yu Ming

N1 - Funding Information: This work is funded by the National Science Foundation under Grant IIS-1208420 . The authors thank the assistance from Mr. Ning Huang on the experiments. Publisher Copyright: © 2014 Elsevier Ltd.

PY - 2014/11/1

Y1 - 2014/11/1

N2 - This paper studies accurate control of human arm movement in machine-human cooperative control of GTAW process. An innovative teleoperated virtualized welding platform is utilized to conduct dynamic experiments to correlate the human welder arm movement with the visual signal input. An adaptive ANFIS model is proposed to model the intrinsic nonlinear and time-varying characteristic of the human welder response. A model based predictive control algorithm is then proposed and an analytical solution is derived. Human control experimental results verify that the proposed controller is able to track varying set-points and is robust under measurement and input disturbances.

AB - This paper studies accurate control of human arm movement in machine-human cooperative control of GTAW process. An innovative teleoperated virtualized welding platform is utilized to conduct dynamic experiments to correlate the human welder arm movement with the visual signal input. An adaptive ANFIS model is proposed to model the intrinsic nonlinear and time-varying characteristic of the human welder response. A model based predictive control algorithm is then proposed and an analytical solution is derived. Human control experimental results verify that the proposed controller is able to track varying set-points and is robust under measurement and input disturbances.

KW - ANFIS

KW - GTAW

KW - Machine-human cooperative control

KW - Model-based predictive control

KW - Virtualized welding

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M3 - Article

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VL - 32

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EP - 171

ER -

Control of human arm movement in machine-human cooperative welding process

Abstract

Bibliographical note

Keywords

ASJC Scopus subject areas

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