Batch-to-Batch Rational Feedforward Control: From Iterative Learning to Identification Approaches, With Application to a Wafer Stage

Feedforward control enables high performance for industrial motion systems that perform nonrepeating motion tasks. Recently, learning techniques have been proposed that improve both performance and flexibility to nonrepeating tasks in a batch-to-batch fashion by using a rational parameterization in feedforward control. This paper aims to unify these approaches through a single framework that provides transparent connections and clear differences between the alternatives. Experimental results on an industrial motion system confirm the theoretical findings and illustrate benefits of rational feedforward tuning in motion systems, including preactuation and postactuation.