Stiffness control of a manipulator using a fuzzy model

Moon Ju Kim, Cheol Kwon, Min Kee Park, Mignon Park

Research output: Contribution to conferencePaperpeer-review

Abstract

In this paper, we suggest a method of deciding the PD gains of a stiffness controller using an identification method based on the Takagi-Sugeno's fuzzy model. It is difficult to perform a compliance task due to the characteristics of the robot itself and an uncertain work environment. Therefore, in this paper, we identify a fuzzy model by dividing the relationship of input-output data into several piecewise-linear equations using the Hough transform, which is an image processing method, and by fine-tuning the parameters of the fuzzy model by a gradient-descent method. By using this fuzzy model, we propose a method of designing the PD gains of the stiffness controller. Finally we show the validity of this method by a surface tracking experiment using a paper box.

Original languageEnglish
Pages322-327
Number of pages6
StatePublished - 1995
EventProceedings of the 1995 IEEE/RSJ International Conference on Intelligent Robots and Systems. Part 3 (of 3) - Pittsburgh, PA, USA
Duration: 5 Aug 19959 Aug 1995

Conference

ConferenceProceedings of the 1995 IEEE/RSJ International Conference on Intelligent Robots and Systems. Part 3 (of 3)
CityPittsburgh, PA, USA
Period5/08/959/08/95

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