Force Sensorless Compliance Control of a Lower-limb Exoskeleton Robot

Q4 Computer Science

International Journal of Automation and Smart Technology Pub Date : 2018-03-01 DOI:10.5875/ausmt.v8i1.1565

C. Kuo, A. Yudha, S. Mohapatra

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引用次数: 3

Abstract

Lower limb rehabilitation machines are widely used to enhance the mobility function of elderly people and patients suffering from spinal cord injury and stroke. In this paper, a four degrees of freedom (DOF) lower body exoskeleton with a model-based compensation control framework is proposed to support hip-knee rehabilitation. The exoskeleton control movement is realized by designing a trajectory for each leg movement. A function approximation technique (FAT) based adaptive control is applied to each two DOF legs during a rehabilitation task. Using the FAT based adaptive control, the natural system dynamic is adaptively compensated for without knowing the acceleration feedback and system dynamics. Simulation results show the disturbance observer successfully estimated the user’s applied leg force. The leg force is given as the input to compliance control applied in 2 DOF motors when performing a walking sequence on a treadmill. Moreover, the FAT-based adaptive control outperformed the standard proportional-differential (PD) control and could accommodate different subjects without any changes to control parameters.

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下肢外骨骼机器人的无力传感器柔顺控制

下肢康复机被广泛用于增强老年人和脊髓损伤和中风患者的活动功能。本文提出了一种具有基于模型的补偿控制框架的四自由度下半身外骨骼，以支持髋膝关节康复。外骨骼控制运动是通过为每条腿的运动设计轨迹来实现的。在康复任务中，将基于函数逼近技术（FAT）的自适应控制应用于每两个自由度腿。使用基于FAT的自适应控制，在不知道加速度反馈和系统动力学的情况下，对自然系统动态进行自适应补偿。仿真结果表明，扰动观测器成功地估计了用户施加的腿部力。当在跑步机上执行步行序列时，腿力被作为2自由度电机中应用的顺应性控制的输入。此外，基于FAT的自适应控制优于标准比例微分（PD）控制，并且可以在不改变控制参数的情况下适应不同的受试者。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

International Journal of Automation and Smart Technology Engineering-Electrical and Electronic Engineering

CiteScore

0.70

自引率

0.00%

发文量

审稿时长

16 weeks

期刊介绍： International Journal of Automation and Smart Technology (AUSMT) is a peer-reviewed, open-access journal devoted to publishing research papers in the fields of automation and smart technology. Currently, the journal is abstracted in Scopus, INSPEC and DOAJ (Directory of Open Access Journals). The research areas of the journal include but are not limited to the fields of mechatronics, automation, ambient Intelligence, sensor networks, human-computer interfaces, and robotics. These technologies should be developed with the major purpose to increase the quality of life as well as to work towards environmental, economic and social sustainability for future generations. AUSMT endeavors to provide a worldwide forum for the dynamic exchange of ideas and findings from research of different disciplines from around the world. Also, AUSMT actively seeks to encourage interaction and cooperation between academia and industry along the fields of automation and smart technology. For the aforementioned purposes, AUSMT maps out 5 areas of interests. Each of them represents a pillar for better future life: - Intelligent Automation Technology. - Ambient Intelligence, Context Awareness, and Sensor Networks. - Human-Computer Interface. - Optomechatronic Modules and Systems. - Robotics, Intelligent Devices and Systems.