Asian Journal of Control
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.
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 Engineering & Computer Science Faculty Publications. 450.
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
This work was supported by National Science Foundation grant 1544702.