Muscle tension training method for series elastic actuator (SEA) based on gain-scheduled method

Abstract A muscle tension training device that contains series elastic actuators (SEAs) has high safety and control performance in human–machine interaction equipment. Based on the cascade impedance controller and the electromyographic (EMG) sensor signal, this paper proposes a self-adaptive gain-scheduled algorithm. The algorithm automatically adjusts the stiffness gain value according to the muscle force. Simultaneously the stable gain function of the passivity condition can ensure the interaction stability. A cascade impedance controller is the basis for ensuring the stiffness of the port and the stability of the interaction; the gain-scheduled function is derived based on the acquired EMG signal and the pre-set muscle exercise mode. Therefore, the control structure is highly efficient, safe to use and offers diverse strength training modes. The simulation and experimental results show that the stiffness gain-scheduled controller can accurately achieve matching of the force and port stiffness. Furthermore, the interaction process ensures precise stability. The gain-scheduled method can adjust the contact stiffness in real time according to the needs of the experimenter. It changes the way muscles exercise under the original constant stiffness. This method that has a personalized exercise feature provides a new solution for improving dynamic training.