Modelling of extended de-weight fuzzy control for an upper-limb exoskeleton
Performing heavy physical tasks, overhead work and long working hours are some examples of activities that can lead to musculoskeletal problems in humans. To overcome this issue, automated robots such as the upper-limb exoskeleton is used to assist humans while performing tasks. However, several con...
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2-s2.0-85104966885 Ali S.K.; Hussin M.; Hadi M.S.; Tokhi M.O. Modelling of extended de-weight fuzzy control for an upper-limb exoskeleton 2021 Journal of Vibroengineering 23 2 10.21595/jve.2020.21481 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85104966885&doi=10.21595%2fjve.2020.21481&partnerID=40&md5=839b81d6600e4c64eb26243c48757b02 Performing heavy physical tasks, overhead work and long working hours are some examples of activities that can lead to musculoskeletal problems in humans. To overcome this issue, automated robots such as the upper-limb exoskeleton is used to assist humans while performing tasks. However, several concerns in developing the exoskeleton have been raised such as the control strategies used. In this study, a control strategy known as the extended de-weight fuzz was proposed to ensure that the exoskeleton could be maneuvered to the desired position with the least number of errors and minimum torque requirement. The extended de-weight fuzzy is a combination of the fuzzy-based PD and fuzzy-based de-weight controller systems. The extended de-weight fuzzy was then compared with the fuzzy-based PD and PID controllers, and the performances of these controllers were compared in terms of their deviations and required torques to perform tasks. The findings show that the proposed control strategy performs better than the fuzzy-based PD and PID controller systems. © 2020 Siti Khadijah Ali, et al. EXTRICA 13928716 English Article All Open Access; Gold Open Access |
author |
Ali S.K.; Hussin M.; Hadi M.S.; Tokhi M.O. |
spellingShingle |
Ali S.K.; Hussin M.; Hadi M.S.; Tokhi M.O. Modelling of extended de-weight fuzzy control for an upper-limb exoskeleton |
author_facet |
Ali S.K.; Hussin M.; Hadi M.S.; Tokhi M.O. |
author_sort |
Ali S.K.; Hussin M.; Hadi M.S.; Tokhi M.O. |
title |
Modelling of extended de-weight fuzzy control for an upper-limb exoskeleton |
title_short |
Modelling of extended de-weight fuzzy control for an upper-limb exoskeleton |
title_full |
Modelling of extended de-weight fuzzy control for an upper-limb exoskeleton |
title_fullStr |
Modelling of extended de-weight fuzzy control for an upper-limb exoskeleton |
title_full_unstemmed |
Modelling of extended de-weight fuzzy control for an upper-limb exoskeleton |
title_sort |
Modelling of extended de-weight fuzzy control for an upper-limb exoskeleton |
publishDate |
2021 |
container_title |
Journal of Vibroengineering |
container_volume |
23 |
container_issue |
2 |
doi_str_mv |
10.21595/jve.2020.21481 |
url |
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85104966885&doi=10.21595%2fjve.2020.21481&partnerID=40&md5=839b81d6600e4c64eb26243c48757b02 |
description |
Performing heavy physical tasks, overhead work and long working hours are some examples of activities that can lead to musculoskeletal problems in humans. To overcome this issue, automated robots such as the upper-limb exoskeleton is used to assist humans while performing tasks. However, several concerns in developing the exoskeleton have been raised such as the control strategies used. In this study, a control strategy known as the extended de-weight fuzz was proposed to ensure that the exoskeleton could be maneuvered to the desired position with the least number of errors and minimum torque requirement. The extended de-weight fuzzy is a combination of the fuzzy-based PD and fuzzy-based de-weight controller systems. The extended de-weight fuzzy was then compared with the fuzzy-based PD and PID controllers, and the performances of these controllers were compared in terms of their deviations and required torques to perform tasks. The findings show that the proposed control strategy performs better than the fuzzy-based PD and PID controller systems. © 2020 Siti Khadijah Ali, et al. |
publisher |
EXTRICA |
issn |
13928716 |
language |
English |
format |
Article |
accesstype |
All Open Access; Gold Open Access |
record_format |
scopus |
collection |
Scopus |
_version_ |
1809677895082180608 |