A survey of iterative learning control

TLDR

Iterative learning control, now in its third decade, has matured with many algorithms beyond this survey, addressing stability, performance, transient learning, and robustness through popular design techniques. This survey aims to provide a broad perspective on the major results, ideas, potential, and limitations of ILC over the past two decades. The authors reviewed key analytical and design results in ILC from the past twenty years to give readers a comprehensive view of its concepts and constraints. The survey discusses problems in stability, performance, learning transient behavior, and robustness, and highlights four popular design techniques.

Abstract

This article surveyed the major results in iterative learning control (ILC) analysis and design over the past two decades. Problems in stability, performance, learning transient behavior, and robustness were discussed along with four design techniques that have emerged as among the most popular. The content of this survey was selected to provide the reader with a broad perspective of the important ideas, potential, and limitations of ILC. Indeed, the maturing field of ILC includes many results and learning algorithms beyond the scope of this survey. Though beginning its third decade of active research, the field of ILC shows no sign of slowing down.