Gait Planning And Trajectory Tracking Control Of Lower Limb Exoskeleton Robo

As my country gradually enters into a deeply aging society,the number of patients with lower limb movement disorders is increasing day by day,as a powerful rehabilitation tool for patients with lower limb disabilities,exoskeleton robots are gradually emerging in the public eye.Compared with traditional rehabilitation methods,it has disadvantages such as high cost and poor rehabilitation effect,the lower extremity exoskeleton robot has won the favor of the majority of patients with lower extremity disabilities due to its outstanding advantages of intelligence,science,precision and high rehabilitation efficiency,and has become a key research direction of many scientific research units.As a wearable rehabilitation device,the lower extremity exoskeleton robot’s gait stability and controller tracking accuracy are key issues that need to be solved urgently.Aiming at these two problems,this thesis launched the research on the gait planning and controller design of the lower extremity exoskeleton robot.The main research contents are as follows:(1)In order to establish the kinematics and dynamics abstract model of the lower limb exoskeleton robot more reasonably,the structure and motion characteristics of the human lower limbs were analyzed and studied from the perspective of sports anatomy.Mastering the joint angle change law of the normal gait of the lower limbs of the human body is the theoretical basis for the successful completion of robot gait planning,to this end,a portable gait acquisition system was designed,and volunteers were invited to conduct data acquisition experiments,the movement rules of the lower limbs of the human body during normal walking are analyzed and summarized.(2)The problem of gait trajectory planning for lower extremity exoskeleton robots was addressed,a gait trajectory planning method combining ZMP stability theory and AGA-PSO parameter optimization was designed.First,based on human gait characteristics and ZMP stability theory,gait planning for the start phase,periodic gait phase and stop phase of the lower extremity exoskeleton robot.Then on the basis of the particle swarm optimization algorithm,the AGA-PSO optimization algorithm was designed to optimize the gait parameters.Finally,the optimized gait trajectory was analyzed by ZMP stability,and the stability of the planned gait trajectory was verified by simulation.(3)The problem of tracking control of the trajectory of the trajectory of the lower limbs was targeted,and a neural network sliding mold controller was designed.Consider the influence of external interference and other factors,the robot system was analyzed by the Lagrange method.Then a sliding mode controller is designed based on the dynamic model,and the approach speed of the system was accelerated by constructing the reaching law.In order to further enhance the controller effect,the neural network was introduced to model the uncertain term compensation approximation of the system,so a neural network sliding mode controller was constructed.Experimental simulation results show that,compared with the sliding mode controller,the designed neural network sliding mode controller tracking accuracy and dynamic quality of the system were improved,and the effective gait trajectory tracking was realized.(4)The experimental platform was built to verify the designed theoretical algorithm.The experimental platform for the lower extremity exoskeleton robot was built,and the hardware design,software design and control system principle of the experimental equipment were introduced.Gait trajectory tracking experiment based on theoretical algorithm and experimental platform,experimental results show,the lower extremity exoskeleton robot can effectively track the desired gait trajectory and maintain stability,and the feasibility of the designed theoretical algorithm was verified.