Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
815821 | Ain Shams Engineering Journal | 2013 | 25 Pages |
Abstract
This paper presents a new neuro-fuzzy controller for robot manipulators. First, an inductive learning technique is applied to generate the required inverse modeling rules from input/output data recorded in the off-line structure learning phase. Second, a fully differentiable fuzzy neural network is developed to construct the inverse dynamics part of the controller for the online parameter learning phase. Finally, a fuzzy-PID-like incremental controller was employed as Feedback servo controller. The proposed control system was tested using dynamic model of a six-axis industrial robot. The control system showed good results compared to the conventional PID individual joint controller.
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Physical Sciences and Engineering
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Engineering (General)
Authors
A.A. Fahmy, A.M. Abdel Ghany,