外骨骼
控制理论(社会学)
弹道
执行机构
机器人
控制器(灌溉)
惯性
扭矩
计算机科学
工程类
控制工程
模拟
人工智能
控制(管理)
物理
天文
热力学
经典力学
农学
生物
作者
Yana Shu,Yu Chen,Xuan Zhang,Zhang Shi-sheng,Gong Chen,Jing Ye,Xiang Li
标识
DOI:10.1109/iros55552.2023.10342056
摘要
The advantages of cable-driven exoskeleton robots with series elastic actuators can be summarized in twofold: 1) the inertia of the robot joint is relatively low, which is more friendly for human-robot interaction; 2) the elastic element is tolerant to impacts and hence provides structural safety. As trade-offs, the overall dynamic model of such a system is of high order and subject to both unmodelled disturbances (due to the cable-driven mechanism) and external torques (due to the human-robot interaction), opening up challenges for the controller development. This paper proposes a new trajectory-tracking control scheme for cable-driven upper-limb exoskeleton robots with series elastic actuators. The control objectives are achieved in two stages: Stage I is to approximate then compensate for unmodelled disturbances with iterative learning techniques; Stage II is to employ a suboptimal model predictive controller to drive the robot to track the desired trajectory. While controlling such a robot is not trivial, the proposed control scheme exhibits the advantages of force-sensorlessness, high accuracy, and low complexity compared with other methods in the real-world experiments.
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