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A robust iterative learning controlling strategy dedicate to mini-LED mass transfer
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Huang, Chengsi, Li, Hongcheng, Liao, Zhishen, Lin, Zhihang, Tang, Hui and Tian, Yanling (2022) A robust iterative learning controlling strategy dedicate to mini-LED mass transfer. In: IEEE International Conference on Manipulation, Manufacturing and Measurement on the Nanoscale (3M-NANO), Tianjin, China, 08-12 Aug 2022. Published in: 2022 IEEE International Conference on Manipulation, Manufacturing and Measurement on the Nanoscale (3M-NANO) pp. 190-195. ISBN 9781665475440. doi:10.1109/3m-nano56083.2022.9941561 ISSN 2373-5422.
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Official URL: http://dx.doi.org/10.1109/10.1109/3m-nano56083.202...
Abstract
With the rapid development of Mini-LED display applications, higher requirements have been placed on the chip mass transfer technology. However, due to the intermittent transfer form, the current chip method with a mechanical ejector pin is difficult to meet the requirements of high accuracy and fast response. To this end, a novel compliant 2-degree of freedom (DOF) ejector pin mechanism for Mini-LED chip mass transfer has been developed. In order to achieve high tracking accuracy, an Iterative Learning Control (ILC) strategy has been implemented and its effectiveness has been verified. However, as a repetitive learning controller, the random disturbances cannot be addressed by ILC, including sensor noise and initial state error. Therefore, a robust ILC strategy has been designed in this paper to deal with random disturbances and improve the tracking accuracy during the learning process. Firstly, in accordance with a multi-boundary mapping criterion, the desired poles of the system are designed to optimize the dynamic performances. Then, the ILC is combined with a pole placement controller (PPC), which is designed by solving the compensator equation and embeds an internal model of the reference signal to enhance the robustness. Finally, a series of experiments are carried out and the experimental results indicate that the proposed control strategy reduces the tracking error during the learning process. Furthermore, thanks to the PPC, the system can track the reference trajectory with robustness.
| Item Type: | Conference Item (Paper) | ||||||
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| Divisions: | Faculty of Science, Engineering and Medicine > Engineering > Engineering | ||||||
| SWORD Depositor: | Library Publications Router | ||||||
| Journal or Publication Title: | 2022 IEEE International Conference on Manipulation, Manufacturing and Measurement on the Nanoscale (3M-NANO) | ||||||
| Publisher: | IEEE | ||||||
| ISBN: | 9781665475440 | ||||||
| ISSN: | 2373-5422 | ||||||
| Official Date: | 16 November 2022 | ||||||
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| Page Range: | pp. 190-195 | ||||||
| DOI: | 10.1109/3m-nano56083.2022.9941561 | ||||||
| Status: | Peer Reviewed | ||||||
| Publication Status: | Published | ||||||
| Access rights to Published version: | Restricted or Subscription Access | ||||||
| Copyright Holders: | IEEE | ||||||
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| Conference Paper Type: | Paper | ||||||
| Title of Event: | IEEE International Conference on Manipulation, Manufacturing and Measurement on the Nanoscale (3M-NANO) | ||||||
| Type of Event: | Conference | ||||||
| Location of Event: | Tianjin, China | ||||||
| Date(s) of Event: | 08-12 Aug 2022 | ||||||
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