Iterative Learning Control for Image Based Visual Servoing Applications

Fabrication of nano/micro-scale functional devices, in the context of a continuous or semi-continuous manufacturing process, is often performed via successive processes in multiple localized zones. As the substrate traverses downstream in the process flow, proper registration of the preexisting features is necessary prior to entering the next fabrication zone in order to accurately complement previous manufacturing steps. In this work, we consider a 2D planar arrangement where the substrate can be panned and oriented and we performed a direct visual servoing technique to correct both the pose and the translational alignment of a pre-existing feature. Based on the recorded image data, Iterative Learning Control (ILC) is implemented on top of the feedback controller to simultaneously improve the position and orientation tracking precision of the feature.