PD-Type Sampled-Data Iterative Learning Control for Nonlinear Systems with Time Delays and Uncertain Disturbances

In this paper, a PD-type sampled-data iterative learning control algorithm is proposed for a class of nonlinear systems with time delays and uncertain disturbances, including random input disturbance and random output measurement noise. By introducing Taloy´ s norm, a rigorous proof is given for the convergence at each sampling point. A sufficient condition is derived to ensure that the real output can track the desired trajectory within a small error if the sampling period is small enough. At last, simulation result illustrates the validity of the proposed control law.