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Robust Control Strategy of Gradient Magnetic Drive for Microrobots Based on Extended State Observer

Microrobots have great application potential in the biomedical field, to realize the precision and efficiency of microrobots in vivo is research focus in this field. Microrobots are accompanied by various disturbances in complex environment. These disturbances will affect the motion control of micro...

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Autores principales: Lu, Jiawei, Liu, Yueyue, Huang, Wentao, Bi, Kaitao, Zhu, Yixin, Fan, Qigao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AAAS 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9619236/
https://www.ncbi.nlm.nih.gov/pubmed/36320320
http://dx.doi.org/10.34133/2022/9835014
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author Lu, Jiawei
Liu, Yueyue
Huang, Wentao
Bi, Kaitao
Zhu, Yixin
Fan, Qigao
author_facet Lu, Jiawei
Liu, Yueyue
Huang, Wentao
Bi, Kaitao
Zhu, Yixin
Fan, Qigao
author_sort Lu, Jiawei
collection PubMed
description Microrobots have great application potential in the biomedical field, to realize the precision and efficiency of microrobots in vivo is research focus in this field. Microrobots are accompanied by various disturbances in complex environment. These disturbances will affect the motion control of microrobots, resulting in the inability of the micromanipulation tasks to be completed effectively. To this end, a robust motion control method is proposed for precise path tracking of microrobots in this paper. The extended state observer (ESO) is used to estimate the total disturbances and uncertainties of the system. A path tracking controller is designed by combining sliding mode control (SMC) and disturbances compensation, which is used to eliminate the total disturbances of the system and realize the fast and accurate path tracking of microrobots. Finally, the path tracking experiments are implemented in the gradient magnetic field drive system. The experimental results show that the mean absolute error of the path tracking for microrobots in a simulated vascular structure is less than 14 μm, and the root mean square error is less than 17 μm by using the robust control method proposed in this paper. Compared with the traditional PID control method, it can better suppress external disturbances and uncertainties of the system and improve the path tracking accuracy of microrobots effectively. It shows stronger anti-interference ability and robustness.
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spelling pubmed-96192362022-10-31 Robust Control Strategy of Gradient Magnetic Drive for Microrobots Based on Extended State Observer Lu, Jiawei Liu, Yueyue Huang, Wentao Bi, Kaitao Zhu, Yixin Fan, Qigao Cyborg Bionic Syst Research Article Microrobots have great application potential in the biomedical field, to realize the precision and efficiency of microrobots in vivo is research focus in this field. Microrobots are accompanied by various disturbances in complex environment. These disturbances will affect the motion control of microrobots, resulting in the inability of the micromanipulation tasks to be completed effectively. To this end, a robust motion control method is proposed for precise path tracking of microrobots in this paper. The extended state observer (ESO) is used to estimate the total disturbances and uncertainties of the system. A path tracking controller is designed by combining sliding mode control (SMC) and disturbances compensation, which is used to eliminate the total disturbances of the system and realize the fast and accurate path tracking of microrobots. Finally, the path tracking experiments are implemented in the gradient magnetic field drive system. The experimental results show that the mean absolute error of the path tracking for microrobots in a simulated vascular structure is less than 14 μm, and the root mean square error is less than 17 μm by using the robust control method proposed in this paper. Compared with the traditional PID control method, it can better suppress external disturbances and uncertainties of the system and improve the path tracking accuracy of microrobots effectively. It shows stronger anti-interference ability and robustness. AAAS 2022-10-21 /pmc/articles/PMC9619236/ /pubmed/36320320 http://dx.doi.org/10.34133/2022/9835014 Text en Copyright © 2022 Jiawei Lu et al. https://creativecommons.org/licenses/by/4.0/Exclusive Licensee Beijing Institute of Technology Press. Distributed under a Creative Commons Attribution License (CC BY 4.0).
spellingShingle Research Article
Lu, Jiawei
Liu, Yueyue
Huang, Wentao
Bi, Kaitao
Zhu, Yixin
Fan, Qigao
Robust Control Strategy of Gradient Magnetic Drive for Microrobots Based on Extended State Observer
title Robust Control Strategy of Gradient Magnetic Drive for Microrobots Based on Extended State Observer
title_full Robust Control Strategy of Gradient Magnetic Drive for Microrobots Based on Extended State Observer
title_fullStr Robust Control Strategy of Gradient Magnetic Drive for Microrobots Based on Extended State Observer
title_full_unstemmed Robust Control Strategy of Gradient Magnetic Drive for Microrobots Based on Extended State Observer
title_short Robust Control Strategy of Gradient Magnetic Drive for Microrobots Based on Extended State Observer
title_sort robust control strategy of gradient magnetic drive for microrobots based on extended state observer
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9619236/
https://www.ncbi.nlm.nih.gov/pubmed/36320320
http://dx.doi.org/10.34133/2022/9835014
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