Master-Slave Upper-limb Exoskeleton Rehabilitation Robot Training Control Method Based on Fuzzy Compensation

For the problems of the master-slave upper-limb exoskeleton rehabilitation robot, such as the information acquisition of the main arm, and the rapid response of the slave arm, this paper proposes a motion intention modeling method based on the information of joint pose, speed and force/torque, and a control strategy of rehabilitation training based on fuzzy compensation. Firstly, a structure of master-slave dual arm isomorphic rehabilitation robot is proposed according to the principle of ergonomics. Then the kinematics model of the master-slave arm is set up in Cartesian space using D-H algorithm, where the mapping relationship from the motion intention information of the patient's healthy limb to the action of the slave arm joints is given for human-machine cooperation. The patient-master-slave arm cooperative control strategy is then proposed based on the fuzzy compensation algorithm, taking the moment of the patient's intentional motion as the input parameter. The stability of the control system is finally proved by Lyapunov theorem. The simulation results show that the slave arm of the rehabilitation robot can follow the motion of the master arm according to the patient's motion intention, and effectively avoid the misoperation and the secondary injury to the affected limb. The experiment verifies that the slave arm has a good trajectory approximation effect and its trajectory is smooth without severe fluctuation.