Nonlinear system identification of rapid thermal processing

Identification of rapid thermal processing parameters is examined to find a more accurate model to predict and control the temperature of semiconductor wafers during processing. In this paper, a Wiener model is applied to identify the significant dynamics of an RTP system. A recursive method is developed to simultaneously estimate the model parameters and states with respect to parameter variation in RTP systems under process noise. The identification result shows that the model's prediction error was greatly reduced as compared to a linear model. The proposed method can also be easily applied to model-based adaptive control.