Compare Fuzzy Interpolation Algorithm with Other Interpolation Methods Used in Industrial Applications

نویسندگان

  • Gerald Agbegha
  • Nailong Guo
  • Ying Bai
  • Johnson C. Smith
چکیده

A novel interpolation algorithm, fuzzy interpolation, is presented and compared with other popular interpolation methods widely implemented in industrial and manufacturing applications. Different interpolation algorithms have been developed, reported and implemented in many industrial applications in recent years. Most of them are based on looking for the optimal interpolation trajectories based on some known values on given points around a workspace. However, it is rare to build an optimal interpolation results based on some random noises, and this is one of the most popular topics in industrial testing and measurement applications. The fuzzy interpolation algorithm (FIA) reported in this paper provides a convenient and simple way to solve this problem and offers more accurate interpolation results based on given position or orientation errors that are randomly distributed in real time. This method can be implemented in many industrial applications, such as manipulators measurements and calibrations, industrial automations and semiconductor manufacturing processes..

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تاریخ انتشار 2011