Optical Manipulation of Biological Cells with a Robot-Tweezers System: A Stochastic Control Approach

Mingyang Xie; Adnan Shakoor; Zhengtian Wu; Baoping Jiang

doi:10.1109/TCSII.2020.2980062

Optical Manipulation of Biological Cells with a Robot-Tweezers System: A Stochastic Control Approach

Mingyang Xie
, Adnan Shakoor^*
, Zhengtian Wu
, Baoping Jiang

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

9 Scopus citations

Abstract

Cell manipulation is a key technique involved in many cell surgery applications. Various automatic frameworks have been developed for optical manipulation of biological cells without consideration of stochastic perturbations, such as Brownian motion. In this brief, a stochastic control scheme for optical manipulation of biological cells is developed. On the basis of the stochastic dynamic model of an optically trapped biological cell, a vectorial backstepping control strategy and its adaptive case is formulated for cell trajectory tracking. The global noise-to-state stability of a closed-loop system in the presence of stochastic perturbations is analyzed. Simulation results demonstrate the performance of the proposed approach.

Original language	English
Article number	9032096
Pages (from-to)	3232-3236
Number of pages	5
Journal	IEEE Transactions on Circuits and Systems II: Express Briefs
Volume	67
Issue number	12
DOIs	https://doi.org/10.1109/TCSII.2020.2980062
State	Published - Dec 2020
Externally published	Yes

Bibliographical note

Publisher Copyright:
© 2004-2012 IEEE.

Keywords

Cell manipulation
backstepping control
optical tweezers
stochastic control

ASJC Scopus subject areas

Electrical and Electronic Engineering

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10.1109/TCSII.2020.2980062

Cite this

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title = "Optical Manipulation of Biological Cells with a Robot-Tweezers System: A Stochastic Control Approach",

abstract = "Cell manipulation is a key technique involved in many cell surgery applications. Various automatic frameworks have been developed for optical manipulation of biological cells without consideration of stochastic perturbations, such as Brownian motion. In this brief, a stochastic control scheme for optical manipulation of biological cells is developed. On the basis of the stochastic dynamic model of an optically trapped biological cell, a vectorial backstepping control strategy and its adaptive case is formulated for cell trajectory tracking. The global noise-to-state stability of a closed-loop system in the presence of stochastic perturbations is analyzed. Simulation results demonstrate the performance of the proposed approach.",

keywords = "Cell manipulation, backstepping control, optical tweezers, stochastic control",

author = "Mingyang Xie and Adnan Shakoor and Zhengtian Wu and Baoping Jiang",

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year = "2020",

month = dec,

doi = "10.1109/TCSII.2020.2980062",

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pages = "3232--3236",

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T1 - Optical Manipulation of Biological Cells with a Robot-Tweezers System

T2 - A Stochastic Control Approach

AU - Xie, Mingyang

AU - Shakoor, Adnan

AU - Wu, Zhengtian

AU - Jiang, Baoping

PY - 2020/12

Y1 - 2020/12

N2 - Cell manipulation is a key technique involved in many cell surgery applications. Various automatic frameworks have been developed for optical manipulation of biological cells without consideration of stochastic perturbations, such as Brownian motion. In this brief, a stochastic control scheme for optical manipulation of biological cells is developed. On the basis of the stochastic dynamic model of an optically trapped biological cell, a vectorial backstepping control strategy and its adaptive case is formulated for cell trajectory tracking. The global noise-to-state stability of a closed-loop system in the presence of stochastic perturbations is analyzed. Simulation results demonstrate the performance of the proposed approach.

AB - Cell manipulation is a key technique involved in many cell surgery applications. Various automatic frameworks have been developed for optical manipulation of biological cells without consideration of stochastic perturbations, such as Brownian motion. In this brief, a stochastic control scheme for optical manipulation of biological cells is developed. On the basis of the stochastic dynamic model of an optically trapped biological cell, a vectorial backstepping control strategy and its adaptive case is formulated for cell trajectory tracking. The global noise-to-state stability of a closed-loop system in the presence of stochastic perturbations is analyzed. Simulation results demonstrate the performance of the proposed approach.

KW - Cell manipulation

KW - backstepping control

KW - optical tweezers

KW - stochastic control

UR - https://www.scopus.com/pages/publications/85097098844

U2 - 10.1109/TCSII.2020.2980062

DO - 10.1109/TCSII.2020.2980062

M3 - Article

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SN - 1549-7747

VL - 67

SP - 3232

EP - 3236

JO - IEEE Transactions on Circuits and Systems II: Express Briefs

JF - IEEE Transactions on Circuits and Systems II: Express Briefs

IS - 12

M1 - 9032096

ER -

Optical Manipulation of Biological Cells with a Robot-Tweezers System: A Stochastic Control Approach

Abstract

Bibliographical note

Keywords

ASJC Scopus subject areas

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