首页> 外文期刊>Neural computation >Repetitive Control for Multi-Joint Arm Movements Based on Virtual Trajectories
【24h】

Repetitive Control for Multi-Joint Arm Movements Based on Virtual Trajectories

机译:基于虚拟轨迹的多关节臂运动的重复控制

获取原文
获取原文并翻译 | 示例

摘要

According to the neuromuscular model of virtual trajectory control, the postures and movements of limbs are performed by shifting the equilibrium positions determined by agonist and antagonist muscle activities. In this study, we develop virtual trajectory control for the reaching movements of a multi-joint arm, introducing a proportional-derivative feedback control scheme. In virtual trajectory control, it is crucial to design a suitable virtual trajectory such that the desired trajectory can be realized. To this end, we propose an algorithm for updating virtual trajectories in repetitive control, which can be regarded as a Newton-like method in a function space. In our repetitive control, the virtual trajectory is corrected without explicit calculation of the arm dynamics, and the actual trajectory converges to the desired trajectory. Using computer simulations, we assessed the proposed repetitive control for the trajectory tracking of a two-link arm. Our results confirmed that when the feedback gains were reasonably high and the sampling time was sufficiently small, the virtual trajectory was adequately updated, and the desired trajectory was almost achieved within approximately 10 iterative trials. We also propose a method for modifying the virtual trajectory to ensure that the formation of the actual trajectory is identical even when the feedback gains are changed. This modification method makes it possible to execute flexible control, in which the feedback gains are effectively altered according to motion tasks.
机译:根据虚拟轨迹控制的神经肌肉模型,肢体的姿势和运动通过转移通过激动剂和拮抗肌肉活动确定的均衡位置来进行。在这项研究中,我们开发了用于多关节臂的达到移动的虚拟轨迹控制,引入了比例衍生反馈控制方案。在虚拟轨迹控制中,设计合适的虚拟轨迹至关重要,使得可以实现所需的轨迹。为此,我们提出了一种用于更新重复控制中的虚拟轨迹的算法,该算法可以被视为函数空间中的类似牛顿的方法。在我们的重复控制中,无需显式计算臂动力学来校正虚拟轨迹,并且实际轨迹会聚到所需的轨迹。使用计算机模拟,我们评估了对双轴臂的轨迹跟踪的建议重复控制。我们的结果证实,当反馈收益合理高并且采样时间足够小时,虚拟轨迹得到充分更新,所需的轨迹几乎在大约10个迭代试验中实现。我们还提出了一种修改虚拟轨迹的方法,以确保即使在改变反馈增益时,即使改变反馈增益,实际轨迹的形成是相同的。该修改方法使得可以执行灵活的控制,其中根据运动任务有效地改变反馈增益。

著录项

  • 来源
    《Neural computation》 |2020年第11期|2212-2236|共25页
  • 作者单位

    Nagoya Univ Grad Sch Engn Nagoya Aichi 4648603 Japan;

    Nagoya Univ Grad Sch Engn Nagoya Aichi 4648603 Japan;

    Aichi Inst Technol Fac Engn Toyota 4700392 Japan;

  • 收录信息 美国《科学引文索引》(SCI);美国《化学文摘》(CA);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号