Research On Lower Limb Exoskeleton Control Strategy Based On Motion Pattern Recognition

In recent years,with the increasingly serious aging of the population,the demand for elderly walking assistance and rehabilitation of people with lower limb movement disorders is gradually increasing.Lower limb exoskeleton robot is a device that exerts external torque and provides power to the body of the wearer.It can be used for lower limb movement rehabilitation of patients with muscle or nerve diseases and improve the body function of the wearer.It is one of the most potent ways to solve the problems of lower limb movement disorders and walking assistance for the elderly.However,most of the existing control strategies for lower limb exoskeleton robots adopt PID control,which is prone to problems such as control lag and poor robustness,and it is difficult to accurately realize trajectory tracking control.To solve the above problems,this paper designs a wearable lower limb exoskeleton robot for the field of power assistance and rehabilitation.Based on the recognition of human motion patterns,a fuzzy PID control strategy is developed based on PID control to improve the robustness of the system.The dynamic simulation model and prototype of the lower limb exoskeleton robot were built,and the trajectory tracking control experiment was carried out to verify the proposed method.Specific research contents are as follows:(1)Lower limb exoskeleton robot system design.Firstly,through the analysis of the movement mechanism of human lower limbs and the gait phase,the freedom degree of each joint was determined,and the appropriate driving mode was selected.Secondly,through the determined driving mode,combined with dynamic simulation analysis,determine the driving motor and driver model;Finally,the overall structure and driving joints of the lower limb exoskeleton robot were designed in combination with the safety,adjustability,and comfort requirements of the lower limb exoskeleton robot design,which laid the foundation for the subsequent construction of the lower limb exoskeleton dynamics simulation model and solid prototype.(2)Gait information acquisition system and motion pattern recognition method design.Firstly,the human gait information acquisition system is designed,including the sensor selection,layout,and wireless transmission system design.Secondly,a motion pattern recognition method based on the threshold method was designed.The phase of human gait was recognized and divided by the data collected by the thin film pressure sensor and the MPU6050 Angle sensor,and then the motion patterns of flat walking,climbing stairs,and descending stairs were recognized.Finally,the accuracy of the recognition algorithm is verified by the acquisition experiment.The experimental results show that the recognition method can identify the phase and movement pattern of human gait more accurately.(3)Control strategy design of lower limb exoskeleton robot.Firstly,the control principle and method of PID control are introduced.Secondly,to solve the problem of overshoot and poor robustness caused by constant control parameters in the PID control process,fuzzy control theory is used to optimize control parameters.Finally,the fuzzy PID controller is designed from the aspects of determining fuzzy subsets and membership functions and establishing fuzzy rules,and the fuzzy PID controller is built by using Matlab fuzzy logic toolbox to prepare for the follow-up dynamic simulation.(4)Simulation analysis and physical verification.First,the lower limb exoskeleton model was imported into Simulink through Solid Works,and the lower limb exoskeleton dynamics simulation model was built based on Simscape.Secondly,dynamic simulation is carried out by PID and fuzzy PID controllers respectively.The performance of the control algorithm is tested by comparing the expected trajectory and robustness of the two controllers.The results show that the fuzzy PID controller has a better trajectory-tracking effect and robustness.Finally,the gait information acquisition system and the lower extremity exoskeleton prototype were combined in Chapter 3 for physical verification.