Adaptive control of the rehabilitation robot with the model uncertainty based on real human gait

The lower limbs exoskeleton rehabilitation robot (LLERR) has been used widely in rehabilitation training of human lower limb injury, where the control research of LLERR is still a hot point in robotics. Therefore, in this paper, a trajectory tracking adaptive control based on human gait is proposed. Where, the real gait trajectory of human body mechanism by using NOKOV motion capture system is used in control system design. In the simulation results, the dynamics model uncertainty are also considered, and the real gait trajectory data of human body is used to the control system. According to the simulation results, when there is uncertainty in the LLERR model, the proposed trajectory tracking adaptive control method can improve the accuracy and reliability of the trajectory tracking, which makes it suitable for different patients. By adaptive control, the uncertain part of the LLERR is compensated, and the structure parameters of the robot are obtained.