ESO-based Iterative Learning Control for Robotic Manipulators with Disturbances: A High-order Fully Actuated Approach

In this paper, we focus on the trajectory tracking of robotic manipulator systems with disturbances. To handle the disturbances, an extended state observer (ESO) is developed. By leveraging the high-order fully actuated (HOFA) approach, the original system is converted into a HOFA system form and a novel iterative learning control (ILC) scheme is proposed, where the convergence analysis is performed under the framework of the composite energy function method. Finally, the effectiveness of the proposed ILC algorithm is verified by an illustrative example.