Research On The Development Of Exoskeleton Lower Limb Rehabilitation Robot System And Its Compliance Control

In view of the current status of global rehabilitation therapy and the limitations of existing lower limb rehabilitation robots,a new type of exoskeleton lower limb rehabilitation robot is developed,which can achieve multi-position rehabilitation training such as recumbent,sitting and standing postures.Various control strategies were adopted to meet patients with different rehabilitation stages.According to the characteristics of lower limbs structure and rehabilitation training requirement,a lower limb exoskeleton rehabilitation robot is designed,which can achieve multi-position rehabilitation training.The design of lower extremity exoskeleton mechanical leg and its human-computer interaction module are introduced in detail.Through the analysis of the mechanism of lower limb gait movement,the natural gait data of different human bodies were collected and fitted into the trajectory function,which served as the reference trajectory for the control of rehabilitation training.The forward and inverse kinematics of the designed exoskeleton legs are analyzed by D-H parameter method,and the dynamic model of the legs is obtained by Lagrange method.The validity of the dynamic model is verified by dynamic simulation analysis.In the early stage of rehabilitation training for patients,aiming at the characteristics of "exoskeleton active" or patient passive control training,a Dual-Mode control algorithm based on PID and fuzzy control is designed.When the system error is large,the dynamic response speed of the system is improved by using fuzzy control;conversely,when the system error is small,the controller is switched to PID control to eliminate steady-state error.The simulation results verify the feasibility of the proposed algorithm and improve the control accuracy effectively.In rehabilitation training recovery stage,in view of the problem of human-machine contact flexibility in the "patient active" or machine passive control training,a PSO impedance control algorithm based on patient's condition fuzzy adaptive is designed.On the basis of optimizing the impedance parameters,by analyzing the patient's condition,a fuzzy adaptive controller is added to compensate the system error and achieve the purpose of compliance control.On the experimental platform of the first generation rehabilitation robot prototype,the limit position test experiment of the lower extremity exoskeleton mechanical leg and the sitting-standing attitude conversion experiment were carried out.The patient passive experiment of Dual-Mode control algorithm based on PID and fuzzy control proves that the designed passive control algorithm can effectively improve the response speed of the system,reduce the steady-state error and improve the robustness of the control.In the patient active experiment based on patient's condition fuzzy adaptive PSO impedance control algorithm,compared with the traditional position impedance control algorithm,the maximum tracking error of the proposed algorithm is reduced by 47.2%,and its cumulative and average error is reduced by 50.7%.It is proved that the proposed algorithm can achieve desired force tracking and effectively improve the accuracy of gait trajectory tracking.