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Iterative Learning Control for Machining with Industrial Robots

In English

Författare

Summary, in English

We consider an iterative learning control (ILC) approach to machining with industrial robots. The robot and the milling process are modeled using system identification methods with a data-driven approach. Two different model-based ILC algorithms are proposed and subsequently experimentally verified in a milling scenario. The difference between the two approaches is the required sensors for acquiring relevant input data for the algorithms. The results from the experiments indicate that the proposed methods have the potential of significantly decreasing the position errors in robotic machining, up to 85% in the considered milling scenario.

Publiceringsår

2014

Språk

Engelska

Sidor

9327-9333

Publikation/Tidskrift/Serie

IFAC-PapersOnLine

Volym

47

Dokumenttyp

Konferensbidrag

Förlag

IFAC

Ämne

  • Control Engineering

Conference name

19th IFAC World Congress, 2014

Conference date

2014-08-24 - 2014-08-29

Conference place

Cape Town, South Africa

Status

Published

Projekt

  • LU Robotics Laboratory
  • SMErobotics
  • LU Robotics Laboratory

Forskningsgrupp

  • LCCC
  • ELLIIT

ISBN/ISSN/Övrigt

  • ISSN: 2405-8963