On adaptive iterative learning control algorithm for discrete-time systems with parametric uncertainties subject to second-order internal model

The adaptive iterative learning control methods is used to control discrete-time systems with time-iteration-varying uncertainties. By exploiting second-order internal model, the time-iteration varying law of uncertainties are derived. A robust adaptive iterative learning control approach is presented for discrete-time systems with exogenous disturbance. The tracking error of the designed adaptive iterative learning control law converges to zero asymptotically as iteration number approaches to infinity even if reference trajectories varying from iteration to iteration. Numerical example is given to validate the adaptive iterative learning control technique.