State Observer-Based Iterative Learning Control of an Uncertain Continuous-Time System

Abstract

Linear systems with the affine model of parametric uncertainty that operate in a repetitive mode are considered. For such systems, a new iterative learning control design method is proposed. This method is based on the use of a full-order state observer and an auxiliary 2D model in the form of a differential repetitive process whose stability guarantees the convergence of the learning process. For obtaining stability conditions, the divergent method of vector Lyapunov functions is used. An example illustrating the features and advantages of the new iterative learning control design method is presented.