Model guided extremum seeking control of electromagnetic micromirrors

In this paper, a simplified dynamic model is constructed to describe the main characteristic of electromagnetic micro-mirror. Then, based on the information provided by the derived simplified model, a model-guided extremum seeking control (MGESC) scheme with backtracking line search is developed, wh...

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Detalles Bibliográficos
Autores principales: Sun, Wanyan, Tan, Yonghong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8413333/
https://www.ncbi.nlm.nih.gov/pubmed/34475513
http://dx.doi.org/10.1038/s41598-021-97098-6
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author Sun, Wanyan
Tan, Yonghong
author_facet Sun, Wanyan
Tan, Yonghong
author_sort Sun, Wanyan
collection PubMed
description In this paper, a simplified dynamic model is constructed to describe the main characteristic of electromagnetic micro-mirror. Then, based on the information provided by the derived simplified model, a model-guided extremum seeking control (MGESC) scheme with backtracking line search is developed, which can automatically estimate the best value of step-size at each search iteration to improve the performance of the control system for target tracking. Then, the convergence of the proposed MGES algorithm is proved. Finally, the experimental results and the simulations are presented to verify the proposed method.
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spelling pubmed-84133332021-09-07 Model guided extremum seeking control of electromagnetic micromirrors Sun, Wanyan Tan, Yonghong Sci Rep Article In this paper, a simplified dynamic model is constructed to describe the main characteristic of electromagnetic micro-mirror. Then, based on the information provided by the derived simplified model, a model-guided extremum seeking control (MGESC) scheme with backtracking line search is developed, which can automatically estimate the best value of step-size at each search iteration to improve the performance of the control system for target tracking. Then, the convergence of the proposed MGES algorithm is proved. Finally, the experimental results and the simulations are presented to verify the proposed method. Nature Publishing Group UK 2021-09-02 /pmc/articles/PMC8413333/ /pubmed/34475513 http://dx.doi.org/10.1038/s41598-021-97098-6 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Sun, Wanyan
Tan, Yonghong
Model guided extremum seeking control of electromagnetic micromirrors
title Model guided extremum seeking control of electromagnetic micromirrors
title_full Model guided extremum seeking control of electromagnetic micromirrors
title_fullStr Model guided extremum seeking control of electromagnetic micromirrors
title_full_unstemmed Model guided extremum seeking control of electromagnetic micromirrors
title_short Model guided extremum seeking control of electromagnetic micromirrors
title_sort model guided extremum seeking control of electromagnetic micromirrors
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8413333/
https://www.ncbi.nlm.nih.gov/pubmed/34475513
http://dx.doi.org/10.1038/s41598-021-97098-6
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