标题:On low-level control strategies of lower extremity exoskeletons with power augmentation
作者:Al-Shuka, Hayder F. N. ;Song, Rui
作者机构:[Al-Shuka, Hayder F. N. ;Song, Rui ] School of Control Science and Engineering, Shandong University, Jinan, China
会议名称:10th International Conference on Advanced Computational Intelligence, ICACI 2018
会议日期:29 March 2018 through 31 March 2018
来源:Proceedings - 2018 10th International Conference on Advanced Computational Intelligence, ICACI 2018
出版年:2018
页码:63-68
DOI:10.1109/ICACI.2018.8377581
关键词:Human-robot interaction; Impedance control; Low-level control; Lower extremity exoskeletons; Powered exoskeletons
摘要:Biomechanical studies prove that the human can undergo hard stresses throughout his/her body especially the low region of the back while lifting/carrying loads. Design of a wearable robot (an exoskeleton) can support and amplify the user power. Three possible points of view are considered for the design of control architecture: (1) minimization of interaction force wrench if possible, (2) modification of reference trajectory of the coupled user-exoskeleton system for compensation of undesirable interaction force wrench, and (3) adding the power assist rate required for empowering the user. To achieve this, three possible levels of control architectures are used: high-level control for capturing the user intention, mid-level control for determining the switching periods of the walking phases, and low-level control for stabilization of the user locomotion. Accordingly, this paper introduces a systematic overview of low-level control strategies adopted for lower extremity exoskeletons with power augmentation. They can be summarized as indirect force control, direct force control, and observer-based control. The features and limitations of each control strategy are described considering some state-of-art powered exoskeleton prototypes. © 2018 IEEE.
收录类别:EI;SCOPUS
Scopus被引频次:1
资源类型:会议论文;期刊论文
原文链接:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85049785637&doi=10.1109%2fICACI.2018.8377581&partnerID=40&md5=7fb13a17ceb14478051cebacb95bf8ae
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