High precision motion control is essential for a wide variety of modern applications. The key to high precision is the incorporation of feedforward information along with typical feedback algorithms. Iterative Learning Control is a very popular method to determine signal-based feedforward control. This talk will discuss recent developments in improving the performance of ILC schemes and their applications to manufacturing applications. In particular, we will motivate the use of ILC schemes with precision manufacturing applications particularly to the nanoscale. We begin by detailing components of a heterogeneous integration approach to the manufacturing of novel electronic and photonic devices by fluidic and ionic transport. This is part of an interdisciplinary research effort involving Materials Science, Physics, Chemistry, Manufacturing, and Controls. The particular process to be detailed is a printing process, termed electro-hydrodynamic Jet (or e-Jet) printing, that is currently superior to most other printing approaches in terms of resolution. After the demonstration of manufacturing processes, a brief introduction to Iterative Learning Control (ILC) will be given. ILC is a novel adaptive technique that allows us to learn repeated trajectories and maximize precision in the automation machinery used for fabrication. After an overview, the rest of the talk will discuss recent developments in ILC for both single-axis and multi-axis systems. We demonstrate the benefits in performance with numerical and experimental results
