Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.731552
Title: Modeling and control of de-weighting upper-limb exoskeleton
Author: Ali, Siti Khadijah
ISNI:       0000 0004 6497 6184
Awarding Body: University of Sheffield
Current Institution: University of Sheffield
Date of Award: 2017
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Abstract:
One of the common problems humans face when performing physical tasks is muscle/joint fatigue. Muscluskelatal disease is identified as one of the major health issues which result from fatigue. Fatigue could also cause performance degradation. Exoskeletons have been identified as means of overcoming such issues. Although, the realisation of exoskeletons for use in rehabilitation, military and industry applications has been widely carried out, however, their realisation for tackling human fatigue is very limited, and those researched are based on biology-based signal input such as electromyography signals. In addition, issues such as the design of upper-limb exoskeleton and conrresponding control approach need to be addressed. Several approaches have been proposed to de-weight the exoskeleton by using mechanical elements such as springs and intelligent control approaches based on fuzzy logic theory. The main aim of the research is to develop humanoid and exoskeleton models, within SimMechanics virtual environment, to perform an initial validation of proposed controller. The target users are people involved in prolonged and repetitive activity in domestic environments. The exoskeleton is aimed to assist and augment the upper-extremity in performing prolonged repetitive tasks by avoiding muscle/joint fatigue. A de-weighting upper extremity exoskeleton mechanism is proposed in this thesis. The de-weighting exoskeleton consists of a fuzzy-based PD and an extended fuzzy controller. To represent the human fatigue condition in the virtual platform, the quasi-static joint-level fatigue model is included. The exoskeleton is activated based on the information received from the human fatigue model. The results achieved demonstrate the capability of the exoskeleton with the proposed control approach in assisting human to carry out prolonged repetitive tasks.
Supervisor: Tokhi, M. Osman ; Lang, Zi-Qiang Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Thesis
EThOS ID: uk.bl.ethos.731552  DOI: Not available
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