Model identification in rapid thermal processing systems

Of the various techniques for controlling the temperature in rapid thermal processing (RTP), model-based control has the greatest potential for attaining the best performance, when the model is accurate. Some system identification methods are introduced to help obtain more accurate models from measured input-output data. For the first identification method, techniques for estimating the parameters (time constant and gain) of a particular physics-based model are presented. For the other, it is shown how to use the input-output measurements to obtain a black-box (autoregressive exogenous) model of the RTP system, which turns out to have better predictive capability. For each problem, the theoretical derivation of the identification technique and assumptions on which it is based are summarized, and experimental results based on data collected from an RTP system are described. Studying the DC response using the identified model led to a reconfiguration of the chamber geometry of the existing RTP system to more effectively distribute the light energy from the lamps