State Estimation For An Agonistic‐Antagonistic Muscle System

Thang Tien Nguyen; Holly Warner; Hung La; Hanieh Mohammadi; Daniel J. Simon; Hanz Richter

doi:10.1002/asjc.1916

State Estimation For An Agonistic‐Antagonistic Muscle System

Thang Tien Nguyen, Holly Warner, Hung La, Hanieh Mohammadi, Daniel J. Simon, Hanz Richter

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

Abstract

<p> Research on assistive technology, rehabilitation, and prosthetics requires the understanding of human machine interaction, in which human muscular properties play a pivotal role. This paper studies a nonlinear agonistic&hyphen;antagonistic muscle system based on the Hill muscle model. To investigate the characteristics of the muscle model, the problem of estimating the state variables and activation signals of the dual muscle system is considered. In this work, parameter uncertainty and unknown inputs are taken into account for the estimation problem. Three observers are presented: a high gain observer, a sliding mode observer, and an adaptive sliding mode observer. Theoretical analysis shows the convergence of the three observers. Numerical simulations reveal that the three observers are comparable and provide reliable estimates.</p>

Original language	American English
Journal	Asian Journal of Control
Volume	21
DOIs	https://doi.org/10.1002/asjc.1916
State	Published - Jan 1 2019

Keywords

Adaptive sliding mode
high gain observer
Hill muscle model
human muscles
state estimation
sliding mode observer

Disciplines

Biomechanical Engineering
Electrical and Computer Engineering

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State Estimation For An Agonistic Antagonistic Muscle SystemFinal published version, 1.7 MBLicense: CC BY

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title = "State Estimation For An Agonistic‐Antagonistic Muscle System",

abstract = " Research on assistive technology, rehabilitation, and prosthetics requires the understanding of human machine interaction, in which human muscular properties play a pivotal role. This paper studies a nonlinear agonistic\&hyphen;antagonistic muscle system based on the Hill muscle model. To investigate the characteristics of the muscle model, the problem of estimating the state variables and activation signals of the dual muscle system is considered. In this work, parameter uncertainty and unknown inputs are taken into account for the estimation problem. Three observers are presented: a high gain observer, a sliding mode observer, and an adaptive sliding mode observer. Theoretical analysis shows the convergence of the three observers. Numerical simulations reveal that the three observers are comparable and provide reliable estimates.",

keywords = "Adaptive sliding mode, high gain observer, Hill muscle model, human muscles, state estimation, sliding mode observer",

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T1 - State Estimation For An Agonistic‐Antagonistic Muscle System

AU - Nguyen, Thang Tien

AU - Warner, Holly

AU - La, Hung

AU - Mohammadi, Hanieh

AU - Simon, Daniel J.

AU - Richter, Hanz

PY - 2019/1/1

Y1 - 2019/1/1

N2 - Research on assistive technology, rehabilitation, and prosthetics requires the understanding of human machine interaction, in which human muscular properties play a pivotal role. This paper studies a nonlinear agonistic&hyphen;antagonistic muscle system based on the Hill muscle model. To investigate the characteristics of the muscle model, the problem of estimating the state variables and activation signals of the dual muscle system is considered. In this work, parameter uncertainty and unknown inputs are taken into account for the estimation problem. Three observers are presented: a high gain observer, a sliding mode observer, and an adaptive sliding mode observer. Theoretical analysis shows the convergence of the three observers. Numerical simulations reveal that the three observers are comparable and provide reliable estimates.

AB - Research on assistive technology, rehabilitation, and prosthetics requires the understanding of human machine interaction, in which human muscular properties play a pivotal role. This paper studies a nonlinear agonistic&hyphen;antagonistic muscle system based on the Hill muscle model. To investigate the characteristics of the muscle model, the problem of estimating the state variables and activation signals of the dual muscle system is considered. In this work, parameter uncertainty and unknown inputs are taken into account for the estimation problem. Three observers are presented: a high gain observer, a sliding mode observer, and an adaptive sliding mode observer. Theoretical analysis shows the convergence of the three observers. Numerical simulations reveal that the three observers are comparable and provide reliable estimates.

KW - Adaptive sliding mode

KW - high gain observer

KW - Hill muscle model

KW - human muscles

KW - state estimation

KW - sliding mode observer

UR - https://engagedscholarship.csuohio.edu/enece_facpub/450

U2 - 10.1002/asjc.1916

DO - 10.1002/asjc.1916

M3 - Article

VL - 21

JO - Asian Journal of Control

JF - Asian Journal of Control

ER -

State Estimation For An Agonistic‐Antagonistic Muscle System

Abstract

Keywords

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