Semi-empirical model-based multivariable iterative learning control of an RTP system

Comprehensive study on control system design for a rapid thermal processing (RTP) equipment has been conducted with the purpose to obtain maximum temperature uniformity across the wafer surface, while precisely tracking a given reference trajectory. The study covers from model development, identification, optimum multivariable iterative learning control (ILC), to reduced-order controller design. The highlight of the study is the ILC technique on the basis of a semi-empirical dynamic radiation model named as T-4-model. It was shown that the T-4-model-based ILC technique can remarkably improve the performance of RTP control compared with the ordinary linear model-based ILC. In addition, reduced-order control methods and the associated optimum sensor location have been addressed. The proposed techniques have been evaluated in an RTP equipment fabricating 8-in wafers.