Terminal iterative learning control with an application to RTPCVD thickness control

Abstract

A special type of iterative learning control (ILC) problem is considered. Due to the insufficient measurement capability in many real control problems such as Rapid Thermal Processing (RTP), it may happen that only the terminal output tracking error instead of the whole output trajectory tracking error is available. In the RTP chemical vapor deposition (CVD) of wafer fab. industry, the ultimate control objective is to control the deposition thickness (DT) at the end of the RTP cycle. The control profile for the next operation cycle has to be updated using the terminal DT tracking error alone. A revised ILC method is proposed to address this terminal output tracking problem. By parameterizing the control profile with a piecewise continuous functional basis, the parameters are updated by a high-order updating scheme. A convergence condition is obtained for a class of uncertain discrete-time time-varying linear systems including the RTPCVD system as the subset. Simulation results for an RTPCVD thickness control problem are presented to demonstrate the effectiveness of the proposed iterative learning scheme.