Iterative learning control design method for linear discrete-time uncertain systems with iteratively periodic factors

In this study, a two-dimensional (2D) H_∞-based method is presented for the iterative learning control (ILC) design problem of a class of linear discrete-time systems with iteratively periodic factors, including initial states, parametric uncertainties, disturbances, measurement noises, and reference trajectories. First, the ILC design problem of the linear systems is described as a controller design problem of 2D uncertain Roesser models. Second, the H_∞ performance of 2D Roesser models is studied under a general boundary condition. Third, an ILC design criterion is presented to achieve the perfect tracking and specified H_∞ performance by using linear matrix inequality approaches. Finally, a numerical example is given to illustrate the efficiency of the proposed ILC design method.