Improving the Quality of Industrial Robot Control Using an Iterative Learning Method with Online Optimal Learning and Intelligent Online Learning Function Parameters
Vo Thu Ha,
Than Thi Thuong,
Vo Quang Vinh
Abstract:It is inevitable that the characteristics of a robot system change inaccurately or cannot be accurately determined during movement and are affected by external disturbances. There are many adaptive control methods, such as the exact linearization method, sliding control, or neural control, to improve the quality of trajectory tracking for a robot’s motion system. However, those methods require a great deal of computation to solve the constrained nonlinear optimization problem. This article first presents some … Show more
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