Adaptive iterative learning control of non-linear MIMO continuous systems with iteration-varying initial error and reference trajectory

Abstract

In this article, an adaptive iterative learning control (ILC) approach is presented to deal with a class of non-linear multi-input multi-output (MIMO) continuous systems with parametric uncertainty. Unlike general ILC techniques, the proposed adaptive ILC approach allows that both the initial error and the reference trajectory are iteration-varying in the ILC process. The designed ILC tracking strategy is to set out a very small initial time interval, and track the iteration-varying reference trajectory beyond the initial time interval. The reference trajectory tracking error beyond the initial time interval can be driven to zero. While the proposed adaptive ILC technique is applied to the repetitive learning control of non-linear MIMO continuous systems, a complete reference trajectory tracking over the whole time interval can be achieved.