A Data-driven Optimal ILC Method Incorporated with Extended State Observer for Nonlinear Discrete-time Repetitive Systems

摘要

In this work, a novel data-driven optimal ILC with an extended state observer for a class of nonlinear non-affine discrete-time repetitive system has been proposed. The main feature of the approach is that the controller design depends merely on the I/O data, and an ESO has been introduced for the estimation of disturbance and uncertainty. The final simulation results verify the effectiveness of the proposed method.