A Comparative Study of Boundary Iterative Learning Control Strategies for Distributed-Parameter Systems

Iterative learning control for lumped-parameter systems is very well developed. Still, comparatively less attention has been directed to applying this method to those whose dynamics evolve in space and time. This paper gives new results in assessing the performance of various iterative learning control designs, focusing on a heat transfer application described by partial differential equations using a network of sensors and actuators.