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Iterative Learning Control for FinTech

2021
Iterative Learning Control (ILC) is a control approach for intricate systems running in repetitive tracking mode. It was firstly introduced by Uchiyama, dated back to 1978 [1], which was not widely spread because it is written in Japanese. In 1984, the paper published by Arimoto et al. [2] has attracted attention from the control community. Since then,
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Iterative Learning Control Design

2015
In this chapter we augment the control structure to further improve tracking accuracy. To do this we exploit the inherently repetitive nature of the rehabilitation process, which involves neurologically impaired participants repeatedly performing tracking movements with their affected arm, with a rest period in between attempts during which their arm ...
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Discrete-Time Iterative Learning Control

2015
In this study the convergence properties of iterative learning control (ILC) algorithms are discussed. The analysis is carried out in a framework using linear iterative systems, which enables several results from the theory of linear systems to be applied. This makes it possible to analyse both first-order and high-order ILC algorithms in both the time
Abidi K, Xu J-X
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Iterative Learning Control—An Overview

2015
This chapter gives the required background on iterative learning control. After introducing the defining characteristic of this form of control, attention is restricted to the laws used in the stroke rehabilitation research.
Chris T. Freeman   +4 more
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Iterative Learning Control

2012
YangQuan Chen   +2 more
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Iterative Learning Control

2007
Hyo-Sung Ahn   +2 more
openaire   +1 more source

Iterative Learning Control and Applications

2017
There is a kind of trajectory tracking problem in practical control. The control task is to find the control law, which makes the output of the controlled object to achieve the zero error of trajectory tracking along the desired trajectory. This tracking problem is a challenging control problem.
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On Finite-Iteration Convergence of Iterative Learning Control

2022 IEEE 11th Data Driven Control and Learning Systems Conference (DDCLS), 2022
Zhiqing Liu, Ronghu Chi, Yang Liu
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Cervical cancer prevention and control in women living with human immunodeficiency virus

Ca-A Cancer Journal for Clinicians, 2021
Philip E Castle, Vikrant V Sahasrabuddhe
exaly  

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