Output-based Adaptive Iterative Learning Control of Uncertain Linear Systems Applied to a Wafer Stage

Iterative learning control (ILC) is an efficient technique applicable to improving the tracking performance of systems that have a repetitive nature. In this paper, point-to-point movements with time-iteration-varying disturbances are considered instead. A new output-based adaptive ILC scheme consisting of an adaptive second-order ILC and an iterative learning estimation of time-iteration-varying disturbances is proposed for a class of linear systems with unknown parameters. The proposed algorithm is used to improve trajectory tracking performance without requiring a plant model or a sensitivity function, and without assuming the initial condition to be zero. In order to verify the proposed algorithm, it is applied to a wafer stage, and the obtained tracking performance is compared with that obtained using a traditional second-order ILC algorithm; better results are obtained using the proposed method.