Adaptive Fuzzy Rules Emulated Networks Controller for 7-DOF Robotic Arm with Time Varying Learning Rate
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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.
KeywordsDiscrete-time adaptive control neuro-fuzzy 7-DOF robotic arm
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