Machine learning model based controller for rapid thermal processing chamber

A processing tool, comprising:

• a chamber;
• a plurality of heater zones at a lid of the chamber;
• a reflector along a bottom of the chamber;
• a substrate support between the plurality of lamps and the reflector;
• and
• a controller coupled to the chamber for controlling a temperature of the substrate, wherein the controller is a model based controller that utilizes a reduced order model (ROM) generated with a dynamic mode decomposition with control (DMDc) process, wherein the controller uses the ROM in a recipe to set a temperature for each zone of the plurality of heater zones and to set a temperature for the reflector plate, and wherein the controller is configured to process a substrate on the substrate support between the plurality of heater zones and the reflector using the recipe.

A method of developing a reduced order model (ROM) for a model based controller, comprising:

• generating a plurality of snapshots, wherein each snapshot includes the temperatures of a plurality of components in a processing tool, the processing tool comprising a plurality of heater zones at a lid of a chamber, and a reflector plate over a bottom of the chamber;
• utilizing a dynamic mode decomposition with control (DMDc) operation in order to extract the ROM from the plurality of snapshots;
• using the ROM in a recipe to set a temperature for each zone of the plurality of heater zones and to set a temperature for the reflector plate;
• and
• processing a substrate between the plurality of heater zones and the reflector using the recipe.