Spatial iterative learning control for motion systems with state-dependent parametric uncertainties

Abstract

In this paper, we present a novel spatial iterative learning control method for a class of uncertain motion systems. The systems are iteratively running along the spatial domain rather than the time domain. The spatial differentiator is introduced such that the motion systems are transformed to the spatial formulation. Based on the composite energy function, the space-based controller is designed. With the adapting law, the state-dependent parametric uncertainties are successfully handled. The boundedness of all signals in closed-loop and the convergence of the tracking error along iteration axis are analyzed rigorously. In the end, an illustrative example is shown to demonstrate the efficacy of the proposed method.