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Design adaptive robust neural network controller for de-icing robot manipulator

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Design adaptive robust neural network controller for de-icing robot manipulator

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In this study, a combination of backstepping technique, double recurrent fuzzy wavelet based on neural networks (DRFWBONNs), adaptive sliding mode controller (ASMC), and adaptive proportional-integral (API) control with dead-zone friction is introduced to the industrial robot manipulator (IRM). Simulation results show the high performance of this control method when compared to adaptive-fuzzy (AF) and proportional-integral-derivative (PID) controller.

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