Nonlinear Model Identification and Control of a Rapid Thermal Processing System for Semiconductor Manufacturing

Abstract

In this paper, an approach to model identification and control of Rapid Thermal Processing (RTP) systems is given for the improvement of controlling the wafer temperature in semiconductor manufacturing. A new parametric identification algorithm based on the nonlinear Wiener model is first applied to identify the RTP system. It includes both subspace method and model parameter optimization. With the iterative optimization procedure, the model parameter converges quickly to the asymptote, and prediction error is greatly reduced. The identification result shows that the Wiener model is superior to a linear model in capturing the RTP dynamics. An EKF-based controller is also designed and implemented for our RTP system. The experiment demonstrates that the controller is capable of steering the dynamic response and thermal uniformity across a wafer over a wide operating envelope.