Performance enhancement of iterative learning control system using disturbance observer

Abstract

Iterative learning control (ILC) has been widely used in industrial applications. However, there are two critical assumptions that limit the use of ILC: a) no non-repetitive disturbance is present; and b) the trajectory needs to be the same every iteration. This paper proposes a control scheme based on the combination of ILC and disturbance observer (DOB) to relax these assumptions. First, the use of DOB attenuates the effects of non-repetitive disturbance on ILC systems. Second, the proposed control scheme can decouple tracking error into two parts: tracking error due to disturbances and tracking error due to a trajectory. The decoupled tracking error then is utilized to properly initialize the ILC for a new trajectory so as to speed up the convergence rate. Simulation results and experimental results of a prototype wafer scanner system demonstrate the effectiveness of the proposed control scheme.