Estimation of model parameters in twisted string actuation system via extended kalman filter

This paper is based on a twisted string actuation system that allows the implementation of simple, powerful, compact and lightweight tendon-based driving systems by using small-size DC motors as actuators characterized by high speed and low torque. This actuation system is well-suited for the implementation in highly-robotic devices due to its properties. The results obtained with this simple and compact actuation system can be used in the field of robotic devices such as robotic hands and exoskeletons. In this paper, the basic working principle of the actuation system is introduced, and the constitutive equations of the system are presented. Then the dynamic model of the actuation system is built, and the dynamic equations are derived. Furthermore. An extended Kalman filter is used in the system in order to estimate the states and some unknown parameters of the system. At last, a control algorithm based on feedback linearization and regulated by the extended Kalman filter is evaluated by the simulation, this algorithm guarantees a high robustness against disturbances.