Research On Control Technology Of Lower Limb Exoskeleton Rehabilitation Robot

Lower limb exoskeleton rehabilitation robot is a new wearable smart device that is usually used for stroke and paraplegia patients and can assist lower limb movement.Its integration of excellent control,rehabilitation medical,human-computer interaction,sensing,embedded technology.How to achieve effective rehabilitation training has become a momentous issue concerned by society and a hot topic of research.This topic mainly studies the control technology of the existing lower limb exoskeleton structure,devise the control system scheme,finish the hardware system devise and equipment selection,carry out the software structure devise and module division,and finish the program flow devise of each module and the code writing,active and passive control strategies are studied and analysed respectively,research from two aspects: theoretical analysis and simulation verification.In terms of hardware,the composition of the overall hardware structure that can achieve control need is planned,and completed the lectotype of controller,servo motor and sensor.In terms of software,the control system software is designed with a modular concept,and the communication tasks,motor control tasks,man-machine interaction tasks and overall system tasks are designed accordingly.Aiming at the disadvantages of traditional PID control in passive control rehabilitation training of lower limb exoskeleton rehabilitation robot,such as poor dynamic performance,an optimized compound control policy is presented.establish a mathematical model of the motor,then the fuzzy PID control policy is proposed with the integration of PID control and fuzzy control,and simulate in MATLAB,results indicate that the fuzzy PID control is able to enhance the dynamic representation of the system.Aiming at the flexibility of the whole man-machine interaction system during the active control training of the lower limb robot,the position-based impedance control policy is designed,and the simulation analysis of trajectory tracking of hip and knee joints.The results indicate that the suggested control algorithm is effective.Figure 66;Table 17;Reference 60...