Robust conditions for iterative learning control in state feedback and output injection paradigm
type: Item
instance of: scholarly article
title: Robust conditions for iterative learning control in state feedback and output injection paradigm
zbMATH Open document ID: 1416.93053
DOI: 10.1155/2019/8023730
author: Muhammad Ali Alsubaie
author: Mubarak KH. Alhajri
author: Tarek S. Altowaim
author: Salem H. Salamah
published in: Journal of Control Science and Engineering
publication date: 2019-06-26T00:00:00Z
review text: Summary: A robust iterative learning control (ILC) design that uses state feedback and output injection for linear time-invariant systems is reintroduced. ILC is a control tool that is used to overcome periodic disturbances in repetitive systems acting on the system input. The design basically depends on the small gain theorem, which suggests isolating a modeled disturbance system and finding the overall transfer function around the delay model. This assures disturbance accommodation if stability conditions are achieved. The reported design has a lack in terms of the uncertainty issue. This study considered the robustness issue by investigating and setting conditions to improve the system performance in the ILC design against a system's unmodeled dynamics. The simulation results obtained for two different systems showed an improvement in the stability margin in the case of system perturbation.
Mathematics Subject Classification ID: 93B35
Mathematics Subject Classification ID: 93B51
Mathematics Subject Classification ID: 93B40
Mathematics Subject Classification ID: 93B52
Mathematics Subject Classification ID: 93C05
zbMATH DE Number: 7073720
zbMATH Keywords: iterative learning control
zbMATH Keywords: robust design
zbMATH Keywords: state feedback
zbMATH Keywords: output injection
zbMATH Keywords: robustness
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1155/2019/8023730
OpenAlex ID: W2910951451
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description: scientific article; zbMATH DE number 7073720