首页> 外文会议>International Conference on Climbing and Walking Robots and the Support Technologies for Mobile Machines >ADAPTIVE GAIT TRAJECTORY BASED ON ITERATIVE LEARNING CONTROL FOR LOWER EXTREMITY REHABILITATION EXOSKELETON
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ADAPTIVE GAIT TRAJECTORY BASED ON ITERATIVE LEARNING CONTROL FOR LOWER EXTREMITY REHABILITATION EXOSKELETON

机译:基于迭代学习控制的自适应步态轨迹基于下肢康复外骨骼的迭代学习控制

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The design of a controller is one of the key tasks and major difficulties in the development of rehabilitation exoskeletons. An algorithm about an adaptive gait trajectory based on the iterative learning control for lower extremity rehabilitation exoskeleton is proposed in this paper. First of all, dynamic model is built up based on the Lagrange equations for the lower extremity rehabilitation exoskeleton. Secondly, an adaptive gait trajectory based on the iterative learning controller is put forward to achieve the active mode of patients. Finally, a simulation experiment is conducted in MATLAB based on the standard gait data which were collected by an optical motion capture system. The simulation results show that the control algorithm can achieve the desired adaptive tracking for joint trajectory and enable patients' active participation in rehabilitation.
机译:控制器的设计是康复外骨骼开发的关键任务和主要困难之一。本文提出了一种关于基于下肢康复外骨骼的迭代学习控制的自适应步态轨迹的算法。首先,基于下肢康复外骨骼的拉格朗日方程建立了动态​​模型。其次,提出了基于迭代学习控制器的自适应步态轨迹来实现患者的活跃模式。最后,基于由光学运动捕获系统收集的标准步态数据在MATLAB中进行仿真实验。仿真结果表明,控制算法可以实现联合轨迹的所需自适应跟踪,使患者积极参与康复。

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