This paper discusses linear iterative learning and repetitive control, presenting general purpose control laws with only a few parameters to tune The method of tuning them is straightforward, maki

http://www.dct.tue.nl/New/Steinbuch/ILC/longman_paper.pdf

Iterative learning control and repetitive control for engineering practice

In this chapter we give an overview of the field of iterative learning control (ILC). We begin with a detailed description of the ILC technique, followed by two illustrative examples that give a flavor of the nature of ILC algorithms and their performance. This is followed by a topical classification of some of the literature of ILC and a discussion of the connection between ILC and other common control paradigms, including conventional feedback control, optimal control, adaptive control, and intelligent control. Next, we give a summary of the major algorithms, results, and applications of ILC given in the literature. This discussion also considers some emerging research topics in ILC. As an example of some of the new directions in ILC theory, we present some of our recent results that show how ILC can be used to force a desired periodic motion in an initially non-repetitive process: a gas-metal arc welding system. The chapter concludes with summary comments on the past, present, and future of ILC.

Iterative Learning Control: An Expository Overview

Control can enable high-bandwidth nanopositioning needed to increase the operating speed of scanning probe microscopes (SPMs). High-speed SPMs can substantially impact the throughput of a wide range of emerging nanosciences and nanotechnologies. In particular, inversion-based control can find the feedforward input needed to account for the positioning dynamics and, thus, achieve the required precision and bandwidth. This article reviews inversion-based feedforward approaches used for high-speed SPMs such as optimal inversion that accounts for model uncertainty and inversion-based iterative control for repetitive applications. The article establishes connections to other existing methods such as zero-phase-error-tracking feedforward and robust feedforward. Additionally the article reviews the use of feedforward in emerging applications such as SPM-based nanoscale combinatorial-science studies, image-based control for subnanometer-scale studies, and imaging of large soft biosamples with SPMs.

https://faculty.washington.edu/devasia/Research/Papers/2009_Feedforward_review_paper.pdf

A review of feedforward control approaches in nanopositioning for high-speed spm

Tracking errors in disk drive systems have a significant repetitive component that is not explicitly taken into account in conventional servo controllers. A modified prototype repetitive controller is applied as a plug-in module to a Winchester disk drive with a preexisting analog feedback controller to demonstrate its efficacy in the reduction of this periodic component. A review of the Winchester disk drive system is included. >

Digital control of repetitive errors in disk drive systems

http://www.mate.tue.nl/mate/pdfs/2041.pdf

Brief Repetitive control for systems with uncertain period-time

Analysis and Synthesis of Discrete-Time Repetitive Controllers

Repetitive control is formulated and analyzed in the discrete-time domain. Sufficiency conditions for the asymptotic convergence of a class of repetitive controllers are given. The "plug-in" repetitive controller is introduced and applied to track-following in a disk-file actuator system. Inter-sample ripples in the tracking error were present when the "plug-in" repetitive controller was installed. The performance is enhanced, however, when the zero-holding device is followed by a low-pass filter or replaced by a delayed first-order hold.

Kok-Kia Chew

Papers

Analysis and Synthesis of Discrete-Time Repetitive Controllers

Discrete-Time Domain Analysis and Synthesis of Repetitive Controllers

Disturbance Rejection Through an External Model