Abstract:
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. With the use of the RFWBONNs structure, the proposed controller not only shows flexibility during parameter adjustment but also demonstrates the ability to compensate for approximate errors. Thereby concluding, the suggested control is accordance for adaptive-robust-neural-network (ARNNs) controller and can be used as supplement and replace of traditional backstepping control.
Năm 2024 
