腱驱动假肢手抓取力跟踪性能控制

摘要

研究腱驱动假肢手抓取力跟踪性能的控制问题,良好的抓取力控制性能是实现假肢手稳定抓取物体的基础.针对腱驱动假肢手手指关节之间存在的高度耦合和非线性因素以及外界扰动和环境知识等不确定问题,分析了假肢手的抓取过程并建立了接触空间的抓握模型,提出一种基于模糊滑模控制的腱驱动假肢手抓握力控制方法.仿真和实验结果表明,相对于传统的PID控制和滑模控制方法,采用基于模糊滑模控制方法能够有效的提高抓取力跟踪精度,并使系统具有较好的鲁棒性.%This article proposes a method for optimization recognition of fault signal of ultra high voltage (UHV) transformer in power system.Firstly,our research selected specific response degree of freedom and ensured that there was specific linear relation among different response signals,then used measuring response to obtain dynamic characteristic of system alone and carried out time-frequency presentation for the signal,namely decomposed the signal.Simulation results show that simulation recognition result is consistent with result obtained by transfer function modal identification.The method has high recognition precision and provides an evidence for modal diagnosis of transformer.