Application of Model Predictive Control to Polishing Robot for Pushing Operation

Nobuaki Endo, Takashi Yoshimi, Koichiro Hayashi, Hiroki Murakami

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Much of the polishing work is done manually by skilled workers. It is not easy to teach robots to perform the detailed work of theirs and to conFigure and operate an appropriate control system to achieve this, and automation of this process has been delayed. Polishing is performed by pressing a rotating tool against the workpiece to be machined. To achieve this motion, PID control is used in the controllers of many robots. However, to determine the appropriate control gain, it is necessary to repeatedly adjust the control gain according to the processing target and processing conditions. The purpose of this research is to introduce Model Predictive Control (MPC) as a new control system for polishing robots. MPC is a control that predicts control output using a model of the control target. Therefore, we considered the target force value could be achieved without changing the MPC parameters when the force condition, a machining condition, is changed. In this paper, control block diagrams were created in MATLAB Simulink to apply MPC. The block diagram was then mounted on the actual machine to check whether it could be pressed with appropriate force, and the differences from PID were evaluated.

Original languageEnglish
Title of host publication2022 22nd International Conference on Control, Automation and Systems, ICCAS 2022
PublisherIEEE Computer Society
Pages518-522
Number of pages5
ISBN (Electronic)9788993215243
DOIs
Publication statusPublished - 2022
Event22nd International Conference on Control, Automation and Systems, ICCAS 2022 - Busan, Korea, Republic of
Duration: 2022 Nov 272022 Dec 1

Publication series

NameInternational Conference on Control, Automation and Systems
Volume2022-November
ISSN (Print)1598-7833

Conference

Conference22nd International Conference on Control, Automation and Systems, ICCAS 2022
Country/TerritoryKorea, Republic of
CityBusan
Period22/11/2722/12/1

Keywords

  • Automation
  • force control
  • Model Predictive Control
  • Polishing
  • robot

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Control and Systems Engineering
  • Electrical and Electronic Engineering

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