On the state estimation of an agonistic-antagonistic muscle system

Thang Nguyen; Holly Warner; Hanieh Mohammadi; Dan Simon; Hanz Richter

doi:10.1115/DSCC2017-5304

On the state estimation of an agonistic-antagonistic muscle system

Thang Nguyen
, Holly Warner
, Hanieh Mohammadi
, Dan Simon
, Hanz Richter

Cleveland State University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Scopus citations

Abstract

In this paper, an agonistic-antagonistic muscle system is presented. This dual muscle system is based on the Hill muscle model. The problem of estimating the state variables and activation signals of the dual muscle system is addressed. A proposed estimation scheme which combines a super-twisting observer and an input estimator is given to provide a solution to the problem. A backstepping control method is used to track a reference trajectory. Numerical results are conducted to show that the relative error for state estimation is about 1% and that for the unknown inputs is about 3% when the measurements of the length of a muscle and its nonlinear spring force are affected by noise profiles whose normalized amplitude is 0.005.

Original language	English
Title of host publication	ASME 2017 Dynamic Systems and Control Conference, DSCC 2017
Place of Publication	usa
Publisher	American Society of Mechanical Engineers
Volume	1
ISBN (Electronic)	9780791858271
DOIs	https://doi.org/10.1115/DSCC2017-5304
State	Published - Jan 1 2017
Event	ASME 2017 Dynamic Systems and Control Conference, DSCC 2017 - Tysons, United States Duration: Oct 11 2017 → Oct 13 2017

Conference

Conference	ASME 2017 Dynamic Systems and Control Conference, DSCC 2017
Country/Territory	United States
City	Tysons
Period	10/11/17 → 10/13/17

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10.1115/DSCC2017-5304

Cite this

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title = "On the state estimation of an agonistic-antagonistic muscle system",

abstract = "In this paper, an agonistic-antagonistic muscle system is presented. This dual muscle system is based on the Hill muscle model. The problem of estimating the state variables and activation signals of the dual muscle system is addressed. A proposed estimation scheme which combines a super-twisting observer and an input estimator is given to provide a solution to the problem. A backstepping control method is used to track a reference trajectory. Numerical results are conducted to show that the relative error for state estimation is about 1\% and that for the unknown inputs is about 3\% when the measurements of the length of a muscle and its nonlinear spring force are affected by noise profiles whose normalized amplitude is 0.005.",

author = "Thang Nguyen and Holly Warner and Hanieh Mohammadi and Dan Simon and Hanz Richter",

year = "2017",

month = jan,

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doi = "10.1115/DSCC2017-5304",

language = "English",

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note = "ASME 2017 Dynamic Systems and Control Conference, DSCC 2017 ; Conference date: 11-10-2017 Through 13-10-2017",

}

Nguyen, T, Warner, H, Mohammadi, H, Simon, D & Richter, H 2017, On the state estimation of an agonistic-antagonistic muscle system. in ASME 2017 Dynamic Systems and Control Conference, DSCC 2017. vol. 1, American Society of Mechanical Engineers, usa, ASME 2017 Dynamic Systems and Control Conference, DSCC 2017, Tysons, United States, 10/11/17. https://doi.org/10.1115/DSCC2017-5304

TY - GEN

T1 - On the state estimation of an agonistic-antagonistic muscle system

AU - Nguyen, Thang

AU - Warner, Holly

AU - Mohammadi, Hanieh

AU - Simon, Dan

AU - Richter, Hanz

PY - 2017/1/1

Y1 - 2017/1/1

N2 - In this paper, an agonistic-antagonistic muscle system is presented. This dual muscle system is based on the Hill muscle model. The problem of estimating the state variables and activation signals of the dual muscle system is addressed. A proposed estimation scheme which combines a super-twisting observer and an input estimator is given to provide a solution to the problem. A backstepping control method is used to track a reference trajectory. Numerical results are conducted to show that the relative error for state estimation is about 1% and that for the unknown inputs is about 3% when the measurements of the length of a muscle and its nonlinear spring force are affected by noise profiles whose normalized amplitude is 0.005.

AB - In this paper, an agonistic-antagonistic muscle system is presented. This dual muscle system is based on the Hill muscle model. The problem of estimating the state variables and activation signals of the dual muscle system is addressed. A proposed estimation scheme which combines a super-twisting observer and an input estimator is given to provide a solution to the problem. A backstepping control method is used to track a reference trajectory. Numerical results are conducted to show that the relative error for state estimation is about 1% and that for the unknown inputs is about 3% when the measurements of the length of a muscle and its nonlinear spring force are affected by noise profiles whose normalized amplitude is 0.005.

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M3 - Conference contribution

VL - 1

BT - ASME 2017 Dynamic Systems and Control Conference, DSCC 2017

PB - American Society of Mechanical Engineers

CY - usa

T2 - ASME 2017 Dynamic Systems and Control Conference, DSCC 2017

Y2 - 11 October 2017 through 13 October 2017

ER -

On the state estimation of an agonistic-antagonistic muscle system

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