Control System Design And Experimental Analysis Of Multi Position Lower Limb Rehabilitation Robot

With the continuous development of medical technology and robot technology,as well as the market demand,the lower limb rehabilitation robot is gradually developed.With its tireless training of high precision and high feedback speed,the rehabilitation cycle of patients is greatly shortened.However,the single training mode and monotonous scene,as well as the lack of specific training like physical therapists,are also the shortcomings of the current lower limb rehabilitation robot,which limits the promotion and application of the lower limb rehabilitation robot.For this reason,based on the feedback idea and the needs of patients to specify personalized training programs,this paper designs and develops the control system of the lower extremity rehabilitation robot.The specific contents are as follows:1.The patient and the robot are regarded as a whole,that is to say,the load of the patient’s leg is applied on the mechanical leg link of the rehabilitation robot.According to the different horizontal and sitting posture of the lower limb rehabilitation robot,the dynamic and kinematic analysis is carried out to provide theoretical basis for the follow-up control system design and motor selection.The movement space of horizontal,inclined horizontal and sitting posture is studied and analyzed respectively,and the trajectory planning of different movement modes is carried out.The corresponding mathematical model is derived,and the simulation analysis is carried out through MATLAB software to judge whether the planned trajectory and movement space meet the needs,so as to provide an important guarantee for the effectiveness and safety of patients’ training.2.In order to improve the diversity of training modes of the lower limb rehabilitation robot and apply it to different patients,the research on the exercise control strategy of rehabilitation training is carried out.The ion motion algorithm proposed recently is used and optimized.At the same time,the traditional PID controller is designed based on the theory that the differential and integral operators of any order can be studied in the fractional order and the derivative has memory,It improves the response speed of multi input and multi output information.According to different training effects,a variety of joint single action,joint linkage passive training mode is designed.The active rehabilitation training control strategy based on the surface EMG signal of the lower limbs and the active control strategy based on the pressure feedback of the foot bottom of the human body are designed.It enriches the mode of rehabilitation training and improves the safety,enthusiasm and sense of participation of patients.3.According to the structural characteristics of the lower limb rehabilitation robot,the design scheme of the control strategy and the scheme requirements of the motion mode,the hardware and software system of the control system are designed in detail and comprehensively,the appropriate electrical components are selected,and the correct wiring is carried out.Using VB6.0,Lab VIEW,MATLB and other programming languages to complete the overall design of the upper computer and lower computer software system of the whole control system.4.Through specific experiments,the control effects of different passive training modes are tested.The simulation results of trajectory planning are analyzed.The validity of active mode based on s EMG and plantar pressure is tested respectively,and the synchronization of passive mode and virtual reality system is verified.In this paper,the control system of multi pose lower limb rehabilitation robot is designed in software and hardware;it has certain characteristics in the construction of multi-sensor fusion information interaction,active and passive training mode based on the surface EMG signal stimulation of lower limb,and active training mode based on pressure information feedback;in the passive training control strategy,it innovatively designs chaos ion based on dynamic inertia weight Fractional Order PID controller optimized by motion algorithm.