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基于关节模拟的绳驱灵巧手控制。

The control of tendon-driven dexterous hands with joint simulation.

机构信息

College of Astronautics, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China.

出版信息

Sensors (Basel). 2014 Jan 20;14(1):1723-39. doi: 10.3390/s140101723.

Abstract

An adaptive impedance control algorithm for tendon-driven dexterous hands is presented. The main idea of this algorithm is to compensate the output of the classical impedance control by an offset that is a proportion-integration-differentiation (PID) expression of force error. The adaptive impedance control can adjust the impedance parameters indirectly when the environment position and stiffness are uncertain. In addition, the position controller and inverse kinematics solver are specially designed for the tendon-driven hand. The performance of the proposed control algorithm is validated by using MATLAB and ADAMS software for joint simulation. ADAMS is a great software for virtual prototype analysis. A tendon-driven hand model is built and a control module is generated in ADAMS. Then the control system is built in MATLAB using the control module. The joint simulation results demonstrate fast response and robustness of the algorithm when the environment is not exactly known, so the algorithm is suitable for the control of tendon-driven dexterous hands.

摘要

提出了一种用于绳驱灵巧手的自适应阻抗控制算法。该算法的主要思想是通过一个补偿项来补偿经典阻抗控制的输出,该补偿项是力误差的比例-积分-微分(PID)表达式。自适应阻抗控制可以在环境位置和刚度不确定时间接调整阻抗参数。此外,位置控制器和运动学逆解求解器是专门为绳驱手设计的。使用 MATLAB 和 ADAMS 软件进行关节仿真验证了所提出的控制算法的性能。ADAMS 是一款用于虚拟样机分析的优秀软件。建立了绳驱手模型,并在 ADAMS 中生成了一个控制模块。然后使用控制模块在 MATLAB 中构建控制系统。关节仿真结果表明,当环境不完全已知时,该算法具有快速响应和鲁棒性,因此该算法适用于绳驱灵巧手的控制。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6487/3926635/6164e394748b/sensors-14-01723f1.jpg

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