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Model-free Control for Continuum Robots Based on an Adaptive Kalman Filter

Research output: Contribution to journalArticle

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Model-free Control for Continuum Robots Based on an Adaptive Kalman Filter. / Li, Minhan; Kang, Rongjie; Branson, David T.; Dai, Jian S.

In: IEEE ASME TRANSACTIONS ON MECHATRONICS, Vol. 23, No. 1, 02.2018.

Research output: Contribution to journalArticle

Harvard

Li, M, Kang, R, Branson, DT & Dai, JS 2018, 'Model-free Control for Continuum Robots Based on an Adaptive Kalman Filter', IEEE ASME TRANSACTIONS ON MECHATRONICS, vol. 23, no. 1. https://doi.org/10.1109/TMECH.2017.2775663

APA

Li, M., Kang, R., Branson, D. T., & Dai, J. S. (2018). Model-free Control for Continuum Robots Based on an Adaptive Kalman Filter. IEEE ASME TRANSACTIONS ON MECHATRONICS, 23(1). https://doi.org/10.1109/TMECH.2017.2775663

Vancouver

Li M, Kang R, Branson DT, Dai JS. Model-free Control for Continuum Robots Based on an Adaptive Kalman Filter. IEEE ASME TRANSACTIONS ON MECHATRONICS. 2018 Feb;23(1). https://doi.org/10.1109/TMECH.2017.2775663

Author

Li, Minhan ; Kang, Rongjie ; Branson, David T. ; Dai, Jian S. / Model-free Control for Continuum Robots Based on an Adaptive Kalman Filter. In: IEEE ASME TRANSACTIONS ON MECHATRONICS. 2018 ; Vol. 23, No. 1.

Bibtex Download

@article{cd62541703194c11ba15d51a85c56734,
title = "Model-free Control for Continuum Robots Based on an Adaptive Kalman Filter",
abstract = "Continuum robots with structural compliance have a promising potential to operate in unstructured environments. However, this structural compliance brings challenges to the controller design due to the existence of considerable uncertainties in the robot and its kinematic model. Typically, a large number of sensors are required to provide the controller the state variables of the robot, including the length of each actuator and position of the robot tip. In this paper, a model-free method based on an adaptive Kalman filter is developed to accomplish path tracking for a continuum robot using only pressures and tip position. As the Kalman filter operates only with a two-step algebraic calculation in every control interval, the low computational load and real time control capability are guaranteed. By adding an optimal vector to the control law, buckling of the robot can also be avoided. Through simulation analysis and experimental validation, this control method shows good robustness against the system uncertainty and external disturbance, and lowers the amount of sensors.",
keywords = "adaptive Kalman filter, anti-disturbance, configuration optimization, Continuum robots",
author = "Minhan Li and Rongjie Kang and Branson, {David T.} and Dai, {Jian S.}",
year = "2018",
month = "2",
doi = "10.1109/TMECH.2017.2775663",
language = "English",
volume = "23",
journal = "IEEE ASME TRANSACTIONS ON MECHATRONICS",
issn = "1083-4435",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
number = "1",

}

RIS (suitable for import to EndNote) Download

TY - JOUR

T1 - Model-free Control for Continuum Robots Based on an Adaptive Kalman Filter

AU - Li, Minhan

AU - Kang, Rongjie

AU - Branson, David T.

AU - Dai, Jian S.

PY - 2018/2

Y1 - 2018/2

N2 - Continuum robots with structural compliance have a promising potential to operate in unstructured environments. However, this structural compliance brings challenges to the controller design due to the existence of considerable uncertainties in the robot and its kinematic model. Typically, a large number of sensors are required to provide the controller the state variables of the robot, including the length of each actuator and position of the robot tip. In this paper, a model-free method based on an adaptive Kalman filter is developed to accomplish path tracking for a continuum robot using only pressures and tip position. As the Kalman filter operates only with a two-step algebraic calculation in every control interval, the low computational load and real time control capability are guaranteed. By adding an optimal vector to the control law, buckling of the robot can also be avoided. Through simulation analysis and experimental validation, this control method shows good robustness against the system uncertainty and external disturbance, and lowers the amount of sensors.

AB - Continuum robots with structural compliance have a promising potential to operate in unstructured environments. However, this structural compliance brings challenges to the controller design due to the existence of considerable uncertainties in the robot and its kinematic model. Typically, a large number of sensors are required to provide the controller the state variables of the robot, including the length of each actuator and position of the robot tip. In this paper, a model-free method based on an adaptive Kalman filter is developed to accomplish path tracking for a continuum robot using only pressures and tip position. As the Kalman filter operates only with a two-step algebraic calculation in every control interval, the low computational load and real time control capability are guaranteed. By adding an optimal vector to the control law, buckling of the robot can also be avoided. Through simulation analysis and experimental validation, this control method shows good robustness against the system uncertainty and external disturbance, and lowers the amount of sensors.

KW - adaptive Kalman filter

KW - anti-disturbance

KW - configuration optimization

KW - Continuum robots

UR - http://www.scopus.com/inward/record.url?scp=85035080320&partnerID=8YFLogxK

U2 - 10.1109/TMECH.2017.2775663

DO - 10.1109/TMECH.2017.2775663

M3 - Article

AN - SCOPUS:85035080320

VL - 23

JO - IEEE ASME TRANSACTIONS ON MECHATRONICS

JF - IEEE ASME TRANSACTIONS ON MECHATRONICS

SN - 1083-4435

IS - 1

ER -

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