Iterative learning control for a class of discrete time nonlinear systems

In this paper, the issues of convergence and robustness of an iterative learning control is addressed for a class of time-varying discrete-time nonlinear dynamic systems. We propose an iterative learning control algorithm and develop a sufficient condition to guarantee the convergence and robustness. It is shown that under this sufficient condition, the iterative learning control can ensure the system outputs, states and control inputs converge to desired trajectories with bounded tracking errors. Furthermore, these errors are functions of repeatibility of initial condition, state and output disturbances. In the absence of such disturbances, the tracking errors can be ensured to go to zero.