Learning Control Approach for Thermal Regulation of Rapid Thermal Processing System

In order to control the temperature distribution on the wafer in a rapid thermal processing system, we develop a learning control approach based on the dominant modes of the system state. Firstly, the dominant modes of the system state are extracted through the K-L method. Galerkin's method is utilized to construct the reduced model of the system from the dominant modes. Then learning control approach is designed based on this reduced model. Simulations are performed by heating the wafer from 300K to 1000K with the proposed control method. Simulation results show that the proposed control method has superb ability to reduce the temperature tracking error and improve the temperature uniformity among the wafer.