ILC-based Internal Model Control of Superheater Steam Temperature

This paper proposes a novel Internal Model Control(IMC) method for the control of superheater steam temperature. The IMC is known for good robustness including handling of systems with time delays. While Iterative Learning Control(ILC) is a strategy for dealing with periodic disturbances. By using a combination of IMC and ILC, their individual advantages are used to increase the robustness against modeling uncertainties and handling time as well as decreasing the influence of the periodic disturbances affecting the superheater steam. Some simulation examples are shown to illustrate performance improvements that can be achieved by the new method over the conventional IMC and PID methods.