Output-based Adaptive Iterative Learning Control of Uncertain Linear Systems Applied to a Wafer Stage

Iterative learning control (ILC) is an efficient technique applicable to improving the tracking performance of systems that have a repetitive nature. In this paper, point-to-point movements with time-iteration-varying disturbances are considered instead. A new output-based adaptive ILC scheme consis...

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Bibliographic Details
Published in:International journal of control, automation, and systems 2022, Automation, and Systems, 20(3), , pp.741-749
Main Authors: Cao, Mingsheng, Bo, Yumeng, Gao, Huibin
Format: Article
Language:English
Subjects:
Adaptive control
Algorithms
Control
Disturbances
Engineering
Iterative methods
Learning
Linear systems
Mechatronics
Regular Papers
Robotics
Tracking
제어계측공학
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Summary:Iterative learning control (ILC) is an efficient technique applicable to improving the tracking performance of systems that have a repetitive nature. In this paper, point-to-point movements with time-iteration-varying disturbances are considered instead. A new output-based adaptive ILC scheme consisting of an adaptive second-order ILC and an iterative learning estimation of time-iteration-varying disturbances is proposed for a class of linear systems with unknown parameters. The proposed algorithm is used to improve trajectory tracking performance without requiring a plant model or a sensitivity function, and without assuming the initial condition to be zero. In order to verify the proposed algorithm, it is applied to a wafer stage, and the obtained tracking performance is compared with that obtained using a traditional second-order ILC algorithm; better results are obtained using the proposed method.
ISSN:1598-6446
2005-4092
DOI:10.1007/s12555-020-0564-9