Iterative Learning Control with Time Domain Prediction using Laguerre Functions

This paper develops an iterative learning control algorithm starting from some recent results in the area of predictive repetitive control. The algorithm uses receding horizon control and Laguerre functions to parameterize the future control trajectory, where the Laguerre functions reduce the number of parameters requiring optimization on-line. Stability of the predictive iterative learning control system is analyzed and conditions on error convergence are established. Supporting experimental results from application to a robot arm are also given.