Suppression of Space-induced Periodic Disturbances using Modified ILC Algorithm

This paper aims to devise a modified iterative learning control (ILC) algorithm with orthogonal projection to enhance the space-induced periodic disturbances rejection performance. Iterative learning control is known as an effective technique for improving the performance of systems that require repetitive work, using the error signal from the previous cycle to update the control input. To make problem tractable, based on structural information about the plant and the disturbances, we determine some basis functions which concentrate the repetitive error. Here, the error signals caused by the disturbances are extracted by projecting the overall error signals onto a subspace spanned by these basis functions. Moreover, a data-driven approach is proposed to design the learning gain. In the end, numerical simulations are provided to demonstrate the efficacy and effectiveness of the proposed algorithm.