Document Type
Article
Publication Date
1-2019
Publication Title
Asian Journal of Control
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‐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.
Repository Citation
Nguyen, Thang Tien; Warner, Holly; La, Hung; Mohammadi, Hanieh; Simon, Daniel J.; and Richter, Hanz, "State Estimation For An Agonistic‐Antagonistic Muscle System" (2019). Electrical and Computer Engineering Faculty Publications. 450.
https://engagedscholarship.csuohio.edu/enece_facpub/450
DOI
10.1002/asjc.1916
Publisher's Statement
This is the accepted version of the following article: Nguyen, T. T., Warner, H., La, H., Mohammadi, H., Simon, D., and Richter, H. ( 2019) State Estimation For An Agonistic‐Antagonistic Muscle System. Asian Journal of Control, 21: 354– 363., which has been published in final form at https://onlinelibrary.wiley.com/doi/full/10.1002/asjc.1916
Volume
21
Issue
1
Comments
This work was supported by National Science Foundation grant 1544702.