论文标题
自然适应法的冗余上肢外骨骼的分散非线性控制
Decentralized Nonlinear Control of Redundant Upper Limb Exoskeleton with Natural Adaptation Law
论文作者
论文摘要
这项工作的目的是利用一种称为虚拟分解控制（VDC）的自适应分散控制方法来控制7度自由度（DOF）右上线骨架外骨骼的最终效果的方向和位置。流行的自适应VDC方法需要调整13N适应性增长以及26N上和下参数边界，其中n是刚体的数量。因此，利用VDC方案控制高DOF机器人，例如7-DOF上LIMB外骨骼可能是一项艰巨的任务。在本文中，采用了一种新的适应函数，即所谓的自然适应定律（NAL），以消除VDC的这些负担，从而使所有13N增益降低到一个并消除对上限和下限的依赖性。在此过程中，基于VDC的动态方程进行了重组，并使惯性参数向量与NAL兼容。然后，利用NAL自适应功能设计新的自适应VDC方案。这种新型的自适应VDC方法可确保无需上限和下限的估计参数的身体一致性条件。最后，通过虚拟稳定性概念和随附的功能证明了该算法的渐近稳定性。实验结果用于证明拟议的新自适应VDC方案的出色性能。
The aim of this work is to utilize an adaptive decentralized control method called virtual decomposition control (VDC) to control the orientation and position of the end-effector of a 7 degrees of freedom (DoF) right-hand upper-limb exoskeleton. The prevailing adaptive VDC approach requires tuning of 13n adaptation gains along with 26n upper and lower parameter bounds, where n is the number of rigid bodies. Therefore, utilizing the VDC scheme to control high DoF robots like the 7-DoF upper-limb exoskeleton can be an arduous task. In this paper, a new adaptation function, so-called natural adaptation law (NAL), is employed to eliminate these burdens from VDC, which results in reducing all 13n gains to one and removing dependency on upper and lower bounds. In doing so, VDC-based dynamic equations are restructured, and inertial parameter vectors are made compatible with NAL. Then, the NAL adaptation function is exploited to design a new adaptive VDC scheme. This novel adaptive VDC approach ensures physical consistency conditions for estimated parameters with no need for upper and lower bounds. Finally, the asymptotic stability of the algorithm is proved with the virtual stability concept and the accompanying function. The experimental results are utilized to demonstrate the excellent performance of the proposed new adaptive VDC scheme.
