Data-driven adaptive iterative learning predictive control

Abstract

A new data-driven predictive iterative learning control(ILC) is proposed for same category discrete nonlinear systems in this work. The controller design only depends on the input/output data of the system and does not need explicit mathematical model. More prediction information along the iteration axis is utilized in the learning control law to improve the control performance. The applicability of the proposed methods is proved by simulation experiments.