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State estimation for an agonistic-antagonistic muscle system. (English) Zbl 1422.93171

Summary: 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.

MSC:

93E10 Estimation and detection in stochastic control theory
92C50 Medical applications (general)
93C10 Nonlinear systems in control theory
93B12 Variable structure systems
93C40 Adaptive control/observation systems
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