Power-Shaping Model-based Control with Feedback Deactivation for Flexible-Joint Robot Interaction
Power-Shaping Model-based Control with Feedback Deactivation for Flexible-Joint Robot Interaction
复制标题
基于功率整形模型的控制，具有反馈停用功能，用于柔性关节机器人交互
DOI：
10.1109/lra.2022.3144781
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发表时间：
2022
影响因子：
5.2
通讯作者：
Jian S. Dai
中科院分区：
文献类型：
--
作者：
Emmanouil Spyrakos-Papastavridis;Zhongtao Fu;Jian S. Dai
本文介绍了一种新颖的控制方法，它是基于模型、功率整形控制（PSC）和反馈停用的综合体。根据假设，柔性关节机器人的比例位置控制可能会影响机器人的性能。
This paper presents a novel control methodology that is based on an amalgamation of model-based, power-shaping control (PSC), and feedback deactivation. It has been hypothesised that proportional position control of flexible-joint robots can impinge on their interactional performance, since position feedback causes a stiffening of the robots joints. In order to reduce reliance upon feedback terms, this work proposes usage of feedforward, model-based control terms, whilst accounting for both the actuator and link coordinates. The introduced PSC signal enables stable tracking control, even when the proportional controllers position error term employs solely non-collocated state feedback. It is also demonstrated that the user can stably deactivate position feedback pertaining to specific joints, in a real-time manner, so as to further enhance interactional performance. However, since feedback deactivation can lead to abrupt generation of unfeasible control signals, a variable impedance control (VIC) technique is proposed to overcome this limitation. Despite VICs potential to inject undesirable amounts of energy into the closed-loop system, an amended PSC term is introduced to guarantee stability preservation. Moreover, to achieve saturation prevention in an energy efficient manner, a novel Lyapunov function is proposed that enables unconstrained modulation of the systems active impedance gains. Experimental results involving the Rethink Robotics Baxter robot corroborate the theoretical stability analyses, in addition to demonstrating that interactional and tracking performance improvements can be achieved via the proposed methodology.
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影响因子：
5.2
作者：
Alexander Dietrich;Xuwei Wu;Kristin Bussmann;C. Ott;A. Albu-Schäffer;S. Stramigioli
通讯作者：
Alexander Dietrich;Xuwei Wu;Kristin Bussmann;C. Ott;A. Albu-Schäffer;S. Stramigioli
影响因子：
5.7
作者：
Florian Petit;Alexander Dietrich;A. Albu-Schäffer
通讯作者：
Florian Petit;Alexander Dietrich;A. Albu-Schäffer
DOI：
10.1109/iros.1992.587350
发表时间：
1992-07
期刊：
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems
影响因子：
--
作者：
Hongnian Yu;L. Seneviratne;S. Earles
通讯作者：
Hongnian Yu;L. Seneviratne;S. Earles
DOI：
10.1109/robot.1995.525448
发表时间：
1995-05
期刊：
Proceedings of 1995 IEEE International Conference on Robotics and Automation
影响因子：
--
作者：
L. Tian;A. Goldenberg
通讯作者：
L. Tian;A. Goldenberg
影响因子：
7.8
作者：
Dongjun Lee;Ke Huang
通讯作者：
Dongjun Lee;Ke Huang