Application of intelligent adaptive tracking control to iterative learning and uncertainty compensation for industrial robot motion systems - Võ Thu Hà; Thân Thị Thương; Bùi Huy Hải; Võ Quang Vinh (Journal of Military Science and Technology, 2023)
A robot motion system always depends on mathematical model parameters that are uncertain or not precisely known and are unavoidably affected by external disturbances. There have been many methods of adaptive control, sustainable control, sliding control, etc., to handle this case. However, those control methods are all based on the uncertain robot mathematical model. At this point, estimating those parameters at least or assuming the parameters are constant and uncertain is necessary. The article presents a control method for moving robots to follow precise orbits without relying entirely on the model, which is a D-type intelligent iterative adaptive controller combined with accurate linearization control. Simulation results for a 2-degree-of-freedom manipulator show that the position error of the final impact joint quickly approaches zero and is accurate.