Iterative learning control for a discrete-time system with changing reference trajectory under uncertainty

This paper considers a linear discrete-time system operating in a repetitive mode to track a reference trajectory with a given accuracy. The system parameters are incompletely known and are described by the affine uncertainty model. In addition, the system is subjected to random disturbances, and measurements are carried out with noise. During system operation, the reference trajectory changes after a given number of repetitions. The resulting transient error may cause a temporary loss of accuracy. We propose a new iterative learning control design method to compensate the transient error. An example illustrates the effectiveness of this method.