Design And Implementation Of Lower Limb Exoskeleton Movement Control System

Lower limb exoskeleton robots are typical wearable robots that have been widely used in military,entertainment,medical rehabilitation,and other fields.In recent years,the number of patients with limb movement disorders caused by stroke or hemiplegia has been increasing.Traditional rehabilitation training methods are inefficient and lack human-machine interaction.Based on this,the thesis designed a lower limb exoskeleton system aimed at providing patients with efficient and intelligent rehabilitation training to make up for the shortcomings of traditional rehabilitation methods.The main research topics of this study include structural and hardware design,identification of dynamic model parameters,design and implementation of active and passive control strategies,and human-machine coupling experiments.The results show that this study has established an effective platform for related rehabilitation training research.To achieve an intelligent control algorithm,a modularized mechanical and hardware platform was first constructed.The system was designed to enable complex interactive control and to consider the expandability of the exoskeleton platform,covering four aspects: mechanical structure,drive system,perception system,and main control unit.For medical rehabilitation purposes,paid particular attention to the safety of patient operation and designed a motor software and hardware limit module.Also,built a software development environment and completed basic module programs for subsequent algorithm implementation.A superior control algorithm requires a corresponding dynamic model.Lagrange’s method was used to establish the dynamic model of the lower limb exoskeleton.At the same time,in consideration of the human-machine interaction goal,the interaction torque between the exoskeleton and the human was modeled by combining the threedimensional force sensor mounted on the exoskeleton.A parameter identification strategy based on neighborhood optimization algorithm is applied to solve the problem of unknown parameters in the model.In order to obtain effective identification results,an excitation trajectory was designed based on the Fourier series and using the condition number as the fitness function.The designed trajectory was used to drive the exoskeleton to collect data,and the optimization algorithm was used to identify the parameters.The validity of the identification results was then verified.Finally,two control modes were implemented for the application of exoskeleton robots in the rehabilitation field: passive control and active control.The passive mode was realized by implementing a feedback controller that allowed patients and the exoskeleton to move along the desired trajectory.The active mode enabled the exoskeleton to follow the patient’s movement intentions and assist in movement.For interactive control,impedance and admittance control strategies were introduced,and the admittance control was implemented.The two control modes were validated by simulation and on-machine experiments.