Abstract
At present, the motion control algorithms of lower limb exoskeleton robots have errors in tracking the desired trajectory of human hip and knee joints, which leads to poor follow-up performance of the human-machine system. Therefore, an iterative learning control algorithm is proposed to track the desired trajectory of human hip and knee joints. In this paper, the experimental platform of lower limb exoskeleton rehabilitation robot is built, and the control system software and hardware design and robot prototype function test are carried out. On this basis, a series of experiments are carried out to verify the rationality of the robot structure and the feasibility of the control method. Firstly, the dynamic model of the lower limb exoskeleton robot is established based on the structure analysis of the human lower limb; secondly, the servo control model of the lower limb exoskeleton robot is established based on the iterative learning control algorithm; finally, the exponential gain closed-loop system is designed by using MATLAB software. The relationship between convergence speed and spectral radius is analyzed, and the expected trajectory of hip joint and knee joint is obtained. The simulation results show that the algorithm can effectively improve the gait tracking accuracy of the lower limb exoskeleton robot and improve the follow-up performance of the human-machine system.
Highlights
With the coming of the 21st century, the aging of the population is becoming more and more serious
In this paper, based on the poor tracking performance of lower limb exoskeleton robot following human motion, iterative learning control algorithm is suitable for repeated work in limited time and can achieve the desired trajectory tracking. erefore, based on iterative learning control algorithm, this paper puts forward the following control model of lower limb exoskeleton robot; through the analysis of human lower limb structure, establishes the dynamic model of lower limb exoskeleton robot; uses iterative learning control algorithm to design the motion control system and carries out convergence analysis; and uses MATLAB software to analyze the human hip
In the stage of single foot support, the driving torque of hip joint and knee joint of swinging leg is larger than that of bipedal support state; because the ankle joint mainly adjusts the direction of human motion in the horizontal plane, the joint driving torque provided in the sagittal plane is smaller [14]. erefore, the swing leg of lower limb exoskeleton robot can be simplified into the swing leg model as shown in Figure 2 in sagittal plane
Summary
With the coming of the 21st century, the aging of the population is becoming more and more serious. E application of derivative control algorithm to hybrid lower limb exoskeleton robot increases the load capacity of human body. E ILC strategy is suitable for the control of such periodic nonlinear systems because of its model independent characteristics and strong self-learning ability, which lays the foundation for the rapid development of ILC. In this paper, based on the poor tracking performance of lower limb exoskeleton robot following human motion, iterative learning control algorithm is suitable for repeated work in limited time and can achieve the desired trajectory tracking. Tracking the desired gait trajectory of the joint and knee joint verifies the superiority of the iterative learning control algorithm and shows good application value
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