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.
- Dynamic Systems and Control Division
On the State Estimation of an Agonistic-Antagonistic Muscle System
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Nguyen, T, Warner, H, Mohammadi, H, Simon, D, & Richter, H. "On the State Estimation of an Agonistic-Antagonistic Muscle System." Proceedings of the ASME 2017 Dynamic Systems and Control Conference. Volume 1: Aerospace Applications; Advances in Control Design Methods; Bio Engineering Applications; Advances in Non-Linear Control; Adaptive and Intelligent Systems Control; Advances in Wind Energy Systems; Advances in Robotics; Assistive and Rehabilitation Robotics; Biomedical and Neural Systems Modeling, Diagnostics, and Control; Bio-Mechatronics and Physical Human Robot; Advanced Driver Assistance Systems and Autonomous Vehicles; Automotive Systems. Tysons, Virginia, USA. October 11–13, 2017. V001T37A005. ASME. https://doi.org/10.1115/DSCC2017-5304
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