基于自适应滑模控制的下肢外骨骼机器人步态轨迹跟踪
Gait Trajectory Tracking of Lower Limb Exoskeleton Robots Based on Adaptive Sliding Mode Control
张奕星1
作者信息
摘要
针对人体膝关节瞬心曲线为可变曲线的问题,设计了双摇杆膝关节结构,采用粒子群算法,以人体膝关节瞬心轨迹为优化目标,得到了膝关节连杆杆长尺寸,并且在SolidWorks中进行3D建模,画出整体下肢外骨骼机器人,采用了一种多输入多输出的控制算法来对髋、膝关节进行同步控制,提升了使用者穿戴下肢外骨骼机器人的舒适性,并与PID算法进行对比.仿真试验结果表明,自适应滑模控制能够同时控制髋、膝关节来达到期望轨迹,相对于PID算法具有更良好的跟踪性能.
Abstract
In response to the problem that the instantaneous center curve of the human knee joint is a variable curve,a double rocker knee joint structure was designed,and particle swarm optimization algorithm was used to optimize the trajectory of the instantaneous center of the human knee joint.The length size of the knee joint connecting rod was obtained,and a 3D modeling was performed in SolidWorks to draw the overall lower limb exoskeleton robot.And a multi input multi output control algorithm was adopted to synchronously control the hip and knee joints,improving the comfort of users wearing lower limb exoskeleton robots.Simulation results showed that adaptive sliding mode control can simultaneously control the hip and knee joints to achieve the desired trajectory.
关键词
膝关节优化/粒子群算法/滑模控制/轨迹跟踪Key words
knee joint optimization/particle swarm optimization algorithm/sliding mode control/trajectory tracking引用本文复制引用
出版年
2024
NETL
NSTL
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