Lower Limb Exoskeleton Robot Coordinated Adaptive Control Research

In recent years,with the increasing demand for lower limb assistance,disability assistance,and medical rehabilitation,the related technologies and products of lower limb exoskeleton robots are developing vigorously.However,most of the existing lower limb exoskeleton robots focus on single gait control in standardized scenes,which has obvious lag and single function,so it is difficult to achieve human-machine collaborative motion and adaptive gait control.Centering on the problem of human-machine non-coordination and poor adaptive gait control effect,this paper designs the structure of the lower limb exoskeleton robot based on ergonomics,combines the human motion intention and the adaptive Central Pattern Generator(CPG),designs the collaborative adaptive CPG control system.And the prototype system is built to carry out the collaborative adaptive CPG trajectory tracking experiment.This paper mainly carries out research work in the following aspects:(1)Lower limb exoskeleton robot system design: Based on practical application requirements,this paper designs the entity prototype of a lower limb exoskeleton robot.First,the Clinical Gait Analysis(CGA)database and Chinese adult body data were investigated,and the design parameters such as structure size,freedom,adjustment device,and joint limit were determined based on the anthropomorphic principle;Secondly,according to the design parameters,the digital model of the lower limb exoskeleton robot is established by Solid Works.Finally,the corresponding collaborative control system framework is designed,based on which,the control system is built from the aspects of hardware and software,laying the foundation for the subsequent physical verification.(2)Kinematics and dynamics modeling of the human-machine system: To make the lower limb exoskeleton robot fit the actual motion Angle of the human body,the human lower limb and its model are simplified according to human gait characteristics.Firstly,the kinematics model of the lower limb exoskeleton robot system was established by the D-H parameter method,and the forward kinematics analysis was carried out to solve the position transformation relationship and Angle expression between each joint;Secondly,the Lagrange method is used to establish the dynamic models of the supporting phase and the swinging phase of the human-machine system respectively,which provides a theoretical basis for the subsequent prototype construction,simulation analysis,and control algorithm.(3)Construction of adaptive central pattern generator system: First,according to the rhythmical and periodic characteristics of human gait,this paper uses the Hopf oscillator to build a CPG network,and optimizes CPG based on Dynamic Hebbian Learning algorithm to learn the gait data curve of each joint;Secondly,a collaborative adaptive CPG controller was constructed by combining human motion intention and adaptive CPG,and CPG network parameters were regulated by real-time detection of human position and pose information,to realize online adjustment of key gait parameters such as step length,stride length and stride frequency of the lower limb exoskeleton robot.(4)Collaborative adaptive control experiment: Based on the movement intention recognition of the user’s limbs,the collaborative adaptive control system designed in this paper is used to conduct the trajectory tracking experiment of the adaptive adjustment of the stride length and pace of the lower limb exoskeleton robot.Firstly,based on the basic gait data and adaptive CPG as input,the virtual prototype of the lower limb exoskeleton robot was co-simulated and analyzed based on ADAMS and Simulink to preliminarily verify the rationality and feasibility of the model;Secondly,the adaptive controller is adjusted and optimized according to the simulation results;Finally,with the input of the cooperative adaptive CPG controller,experiments were conducted to adjust the constant speed,stride length,and stride speed of the lower limb exoskeleton human-machine system.The results show that the collaborative adaptive CPG designed in this paper can realize the adaptive gait control of the lower limb exoskeleton robot.