Segmented iterative learning control strategy for wafer scanner systems

Abstract:

Based on exposure characteristics of the wafer scanner, a segmented iterative learning control strategy is presented. The proposed method inherits the advantage of non-causal iterative learning control, which is full learning of errors. In order to improve the dynamic tracking performance, non-causal learning of errors in the last iteration is implemented during the acceleration phase, which guarantees the fast convergence of the system versus iteration domain. For the purpose of overcoming the weakness of blind learning for non-causal iterative learning control methods, errors are not learnt fully during the constant velocity so that exposure performance does not go bad. It improves the transient performance versus time. In addition, the convergence of the proposed method is analyzed and proved. Combining the numerical example, effectiveness of the method is testified.