A Singleton Type-1 Fuzzy Logic Controller for On-Line Error Compensation During Robotic Welding
Keywords:
Gas Metal Arc Welding (GMAW), industrial robotics, artificial vision, robot path control, fuzzy logicAbstract
During robot welding operations in the manufacturing industry there is a need to modify on-line the welding path due to a mismatch in the position of the components to be welded. These positioning errors are due to multiple factors such as ageing of the components in the conveyor system, clamp fixtures, disturbances, etc. Therefore, robot reprogramming is needed which requires a stop in the production line and consequently an increment in production costs. This article is an extension of [1]a and presents an alternative solution to this problem that involves the use of structured lighting using a low-cost laser beam, a CMOS camera and a Gaussian singleton fuzzy logic controller. To validate the proposed control system, a robotic cell was designed using an industrial KUKA KR16 robot for welding metallic plates. The method was evaluated experimentally under lateral and vertical positioning errors.References
Ignacio Davila-Rios, Ismael Lopez-Juarez, Gerardo M. Mendez, Roman Osorio-Comparan, Gaston Lefranc and Claudio Cubillos (2016); A Fuzzy Approach for on-line Error Compensation During Robotic Welding, Computers Communications and Control (ICCCC), 2016 6th International Conference on, ISBN 978-1-5090-1735-5, IEEE Xplore, DOI:10.1109/ICCCC.2016.7496766, 264- 270. https://doi.org/10.1109/ICCCC.2016.7496766
Menno de Graaf, Ronald Aarts, Ben Jonker, Johan Meijer (2010); Real-time seam tracking for robotic laser welding using trajectory-based control, Control Engineering Practice, 18(8):944-953. https://doi.org/10.1016/j.conengprac.2010.04.001
Tero Santti, Jonne K. Poikonen, Olli Lahdenoja, Mika Laiho, Ari Paasio (2015); Online seam tracking for laser welding with a vision chip and FPGA enabled camera system, IEEE International Symposium on Circuits and Systems (ISCAS), May 2015, 1985 - 1988.
Jinchao Liu, Zhun Fan, Srren Ingvor Olsen, Kim Hardam Christensen, Jens Klcstrup Kristensen (2015); A Real-time Passive Vision System for Robotic Arc Welding, IEEE International Conference on Automation Science and Engineering (CASE), Aug. 2015, 389-394.
T. Ngo, Y. Wang, T.L. Mai, M.H. Nguyen, J. Chen (2012); Robust Adaptive Neural-Fuzzy Network Tracking Control for Robot Manipulator, International Journal of Computer Communications & Control, ISSN 1841-9836, 7(2):341-352.
I. Hartley and A. Zisserman (2004); Multiple View Geometry in Computer Vision, Cambridge University Press, ISBN: 0521540518, second edition, 2004.
J. M. Mendel (2001); Uncertain rule-based fuzzy logic systems: introduction and new directions, Prentice-Hall, Upper Saddle River, NJ, 2001.
John Yen, Reza Langari (1998); Fuzzy Logic: Intelligence, Control and Information, Prentice- Hall), ISBN 0135258170, 1998.
MartÃn del Br io B, Sanz Molina A. (2006); Redes Neuronales y Sistemas Borrosos, 3rd edition, ISBN 978-84-7897-743-7, RA-MA, 2006.
Montgomery D C. (2007); Design and Analysis of Experiments, John Wiley Sons, 6th edition, ISBN-10: 047148735X, 2007.
Published
Issue
Section
License
ONLINE OPEN ACCES: Acces to full text of each article and each issue are allowed for free in respect of Attribution-NonCommercial 4.0 International (CC BY-NC 4.0.
You are free to:
-Share: copy and redistribute the material in any medium or format;
-Adapt: remix, transform, and build upon the material.
The licensor cannot revoke these freedoms as long as you follow the license terms.
DISCLAIMER: The author(s) of each article appearing in International Journal of Computers Communications & Control is/are solely responsible for the content thereof; the publication of an article shall not constitute or be deemed to constitute any representation by the Editors or Agora University Press that the data presented therein are original, correct or sufficient to support the conclusions reached or that the experiment design or methodology is adequate.
