Human Cooperative Control of Lower-limb Robotic Exoskeleton Based on Region Function

A human-cooperative control algorithm based on human region had been proposed in this paper, which enable the subjects change the movements of the lower-limb exoskeleton robots. At first, the kinematic and dynamics of the lower-limb exoskeleton robots is proposed, then we divide the task space into two portion, i.e., a human region, in which human can change the movement of the robots, a robot region, in which the robot drive take the lead. The designed control incorporating adaptive learning technique makes tracking errors convergent while the different region can be switched. By using Lyapunov analysis, we proved the closed-loop system is stable. The experimental results are presented to demonstrate the proposed controller have a good tracking performance.