Formation-Based Decentralized Iterative Learning Cooperative Impedance Control for a Team of Robot Manipulators
Formation-Based Decentralized Iterative Learning Cooperative Impedance Control for a Team of Robot Manipulators
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DOI：
10.1109/tsmc.2022.3189661
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发表时间：
2023-02
期刊：
影响因子：
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通讯作者：
Xu Jin
中科院分区：
文献类型：
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作者：
Xu Jin
在这篇文章中，我们提出了一个新的分散迭代学习合作阻抗控制（ILCIC）架构，以合作控制阻抗的机器人操作器的团队，在一个迭代域。与一个新的定义的邻居阻抗误差，我们提出了一种新的基于编队的合作控制架构，使每个机械手可以实现所需的阻抗模型，即使当一些机械手没有直接访问所需的角度轮廓。此外，期望的角度轮廓以及期望的阻抗模型可以是迭代变化的，这是当团队需要在不同的迭代中执行不同的任务时的重要考虑。通过严格的数学分析，我们证明了当迭代次数增加到无穷大时，每个机械臂的阻抗误差可以一致收敛到零。仿真研究进行了讨论，以进一步说明所讨论的算法的有效性。
We present in this article a new decentralized iterative learning cooperative impedance control (ILCIC) architecture to cooperatively control the impedance for a team of robot manipulators that operate over an iteration domain. With a new definition of the neighborhood impedance error, we propose a novel formation-based cooperative control architecture, so that every manipulator can achieve the desired impedance model, even when some manipulators do not have direct access to the desired angle profiles. Besides, the desired angle profiles as well as the desired impedance model can be iteration varying, which is an important consideration when the team needs to execute different tasks in different iterations. With rigorous mathematical analysis, we show that each manipulator’s impedance error can uniformly converge to zero as the iteration index increases to infinity. A simulation study is discussed in order to further illustrate the effectiveness of the discussed algorithm.