Set-point variation in learning schemes with applications to wafer scanners

This paper presents a finite impulse response strategy to deal with set-point variation in learning schemes. On the basis of converged learning forces obtained with learning control at a specific acceleration set-point profile, a finite impulse response mapping is derived to generalize the learned forces at a specific set-point toward arbitrary set-point profiles, thus relaxing the need for further learning. The above strategy is applied to the motion control systems of a wafer scanner in a multi-input multi-output feed-forward setting, where a variety of set-point profiles is used. Industrial potential is demonstrated via robustness to set-point variation and the improvements obtained in settling-time reduction.