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Adaptive Fuzzy Rules Emulated Networks Controller for 7-DOF Robotic Arm with Time Varying Learning Rate

  • C. Treesatayapun
Chapter
  • 528 Downloads
Part of the Studies in Computational Intelligence book series (SCI, volume 363)

Abstract

This article presents an adaptive controller based on fuzzy rules emulated network (FREN) with the proposed on-line learning algorithm. The human knowledge about the unknown plant, 7- DOF robotic arm in this case, is transferred to be if-then rules for setting the network structure. All adjustable parameters are tuned by the on-line learning mechanism with time varying step size or learning rate. The main theorem is introduced to improve the system performance and stabilization through the variation of learning rate. Experimental system based on Mitsubishi PA-10 is demonstrated the control algorithm validation.

Keywords

Discrete-time adaptive control neuro-fuzzy 7-DOF robotic arm 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • C. Treesatayapun
    • 1
  1. 1.Department of Robotic and ManufacturingCINVESTAV-SaltilloRamos ArizpeMexico

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