Adaptive predictive ANFIS based human arm movement modeling and control in machine-human cooperative GTAW process

Yukang Liu, Yuming Zhang

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

Abstract

Automated Gas Tungsten Arc Welding (GTAW) systems rely on highly costly precision control of welding conditions to produce repeatable results. Comparably, human welders have advantages in versatility and accessibility, yet fatigue and stress build up quickly thus adversely affecting their ability to produce quality welds. This paper proposes an innovative machine-human cooperative control scheme in which a machine algorithm determines (based on model prediction of human and process responses) adjustments to human welder controlled process. As the first study, this paper aims at accurate control of human arm movement. In particular, an innovative teleoperated virtualized welding platform is utilized to conduct dynamic experiments in order to correlate the human welder arm movement to the visual signal input. Linear model is firstly identified and an Adaptive Neuro-Fuzzy Inference System (ANFIS) model is then proposed to improve the model accuracy. To account for the welder's time-varying responses, an adaptive ANFIS model is finally used to model the intrinsic nonlinear and time-varying characteristic of the human welder response. An adaptive nonlinear ANFIS model-based predictive control (MPC) algorithm is then proposed to control the human arm movement. To demonstrate the controller's performance, human control experiments are conducted. Results verified that the proposed controller is able to track varying set-point and under input disturbance.

Original languageEnglish
Title of host publication2015 IEEE Conference on Automation Science and Engineering
Subtitle of host publicationAutomation for a Sustainable Future, CASE 2015
Pages1465-1470
Number of pages6
ISBN (Electronic)9781467381833
DOIs
StatePublished - Oct 7 2015
Event11th IEEE International Conference on Automation Science and Engineering, CASE 2015 - Gothenburg, Sweden
Duration: Aug 24 2015Aug 28 2015

Publication series

NameIEEE International Conference on Automation Science and Engineering
Volume2015-October
ISSN (Print)2161-8070
ISSN (Electronic)2161-8089

Conference

Conference11th IEEE International Conference on Automation Science and Engineering, CASE 2015
Country/TerritorySweden
CityGothenburg
Period8/24/158/28/15

Bibliographical note

Publisher Copyright:
© 2015 IEEE.

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Electrical and Electronic Engineering

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