A Survey of Iterative Learning Control: A Learning-Based Method for High-Performance Tracking Control

Douglas A. Bristow; Marina Tharayil; Andrew G. Alleyne

doi:10.1109/MCS.2006.1636313

A Survey of Iterative Learning Control: A Learning-Based Method for High-Performance Tracking Control

Douglas A. Bristow
, Marina Tharayil
, Andrew G. Alleyne

Mechanical and Aerospace Engineering

Research output: Contribution to journal › Article › peer-review

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.

Original language	American English
Journal	IEEE Control Systems Magazine
DOIs	https://doi.org/10.1109/MCS.2006.1636313
State	Published - Jan 1 2006

Keywords

Adaptive Control
Control System Synthesis
Control Systems Analysis
Feedback
Feedforward
Iterative Methods
Learning Systems
Robust Control

Disciplines

Aerospace Engineering
Mechanical Engineering

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10.1109/MCS.2006.1636313License: Unspecified

https://doi.org/10.1109/MCS.2006.1636313

Cite this

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title = "A Survey of Iterative Learning Control: A Learning-Based Method for High-Performance Tracking Control",

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.",

keywords = "Adaptive Control, Control System Synthesis, Control Systems Analysis, Feedback, Feedforward, Iterative Methods, Learning Systems, Robust Control",

author = "Bristow, \{Douglas A.\} and Marina Tharayil and Alleyne, \{Andrew G.\}",

year = "2006",

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doi = "10.1109/MCS.2006.1636313",

language = "American English",

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Y1 - 2006/1/1

N2 - 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.

AB - 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.

KW - Adaptive Control

KW - Control System Synthesis

KW - Control Systems Analysis

KW - Feedback

KW - Feedforward

KW - Iterative Methods

KW - Learning Systems

KW - Robust Control

UR - https://scholarsmine.mst.edu/mec_aereng_facwork/1328

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DO - 10.1109/MCS.2006.1636313

M3 - Article

JO - IEEE Control Systems Magazine

JF - IEEE Control Systems Magazine

ER -

A Survey of Iterative Learning Control: A Learning-Based Method for High-Performance Tracking Control

Abstract

Keywords

Disciplines

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