Design of Human-Machine Collaborative Control Algorithm for Lower Limb Exoskeleton

Abstract

In order to improve the flexibility and coordination of the exoskeleton robot, aiming at the problems of lower limb exoskeleton's poor adaptability to the external environment and poor humanmachine interaction, the human-machine interaction control technology of the lower limb exoskeleton system driven by flexible bowden cable is studied in this paper. Modeling the dynamics model of the lower limb exoskeleton system driven by double bowden cable, a neural network is used to identify the wearer's movement intentions on the basis of real-time control platform, and an adaptive impedance control strategy is designed to realize the human-machine dynamic coordination. The trajectory following of the exoskeleton is implemented by torque control, and the experiments of assisted walking at different speeds prove that the lower limb exoskeleton has good dynamic adjustment performance and can realize human-machine collaboration well. The evaluation experiment of the exoskeleton's auxiliary effect is carried out, and the EMG signals prove that the human-machine collaborative control algorithm has an auxiliary effect of 5.74%-9.73%.