Research On The Lower-limb Extremity Exoskeleton Robot

There is a urgent demand in the medical field that using extremity exoskeleton robot for helping people who are suffering complete spinal cord injury to standing and locomotion. The exoskeletons also can help patients to reduce complications and pain, and these patients can return to normal life as soon as possible. This paper’s purpose is doing some exploring research on the lower-limb extremity exoskeletons for human locomotion assistance. Including the design of the robot mechanical system, the exoskeleton system kinematics and dynamics analysis, control algorithm research and experimental platform was built and the experimental verification etc.To finish the design of mechanical system, first of all should be clear about the use of special objects, to know the symptom of the spinal cord injury, so that we can lay the foundation of medicine for the design. Secondly, the structure and motion characteristics of the lower limb of the human body is analyzed, and the size of the human body and the range of motion of the lower limb is defined. And then the robot joint degree of freedom is determined, and the appropriate driving mode is selected. This paper finished the design of structure, processed model machine.The purpose of kinematics analysis t is to know the motion characteristics of the robot, and to get the relationship between the end position and the joint angle, and to provide the basis for the selection of the actuator. Based on the analysis of the human locomotion, three kinds of dynamic models are established according to the different stages of human locomotion used Lagrange’s equations, which lays the foundation for the robot control. The dynamics simulation is carried out based on the Adams model, which verifies the correctness of the established dynamic model, and the Adams-MATLAB joint simulation platform is established.The trajectory tracking control of robotic system is based on the Computed Torque Control(CTC) method. However, due to the large disturbance, the dynamic modeling error is large, which leads to the failure of the CTC. On the basis of this proposed a Variable Structure Control(VSC) to compensate the CTC, compensating for the modeling error. For VSC system’s chattering problem, the introduction of the quasi synovial dynamic control, using the saturation function instead of sign function, reduce the chattering effectively. But in VSC the switching gain depends on the system modeling error bound and valuation uncertainty will lead to control system performance degradation, therefore proposes the use of adaptive RBF neural network learning the switching gain in VSC system. These algorithms were proved by Lyapunov stability theory, and verified the control performance of the algorithm through the joint simulation.Finally, the control system were designed based on x PC Target. And the hardware system is introduced in this paper, designed the hardware circuit, and built the block diagram of the system. And this paper began to do some experiments of single joint debugging and multi joint gait tracking experiment, so we could verify the reliability of each module of the system and the feasibility of the algorithm, and find the defects in the design process, and provide guidance for system optimization.