Application of PILC to uncertain nonlinear systems for slowly varying desired trajectories

An application of prediction based iterative learning control (PILC) is presented for tracking control of nonlinear uncertain systems. The desired trajectory is not fixed for all iterations and supposed to vary in the successive iterations. The variations are assumed to be slow. Conditions are derived for the convergence of PILC and it is proved that the uniform boundedness of the final tracking error can be obtained in the presence of uncertainty and slowly varying trajectories. The effectiveness of the proposed PILC is presented by simulations.