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Reverse pneumatic artificial muscles (rPAMs): Modeling, integration, and control

Despite offering many advantages over traditional rigid actuators, soft pneumatic actuators suffer from a lack of comprehensive, computationally efficient models and precise embedded control schemes without bulky flow-control valves and extensive computer hardware. In this article, we consider an in...

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Autores principales: Skorina, Erik H., Luo, Ming, Oo, Wut Yee, Tao, Weijia, Chen, Fuchen, Youssefian, Sina, Rahbar, Nima, Onal, Cagdas D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6193585/
https://www.ncbi.nlm.nih.gov/pubmed/30312314
http://dx.doi.org/10.1371/journal.pone.0204637
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author Skorina, Erik H.
Luo, Ming
Oo, Wut Yee
Tao, Weijia
Chen, Fuchen
Youssefian, Sina
Rahbar, Nima
Onal, Cagdas D.
author_facet Skorina, Erik H.
Luo, Ming
Oo, Wut Yee
Tao, Weijia
Chen, Fuchen
Youssefian, Sina
Rahbar, Nima
Onal, Cagdas D.
author_sort Skorina, Erik H.
collection PubMed
description Despite offering many advantages over traditional rigid actuators, soft pneumatic actuators suffer from a lack of comprehensive, computationally efficient models and precise embedded control schemes without bulky flow-control valves and extensive computer hardware. In this article, we consider an inexpensive and reliable soft linear actuator, called the reverse pneumatic artificial muscle (rPAM), which consists of silicone rubber that is radially constrained by symmetrical double-helix threading. We describe analytical and numerical static models of this actuator, and compare their performance against experimental results. To study the application of rPAMs to operate underlying kinematic linkage skeletons, we consider a single degree-of-freedom revolute joint that is driven antagonistically by two of these actuators. An analytical model is then derived, and its accuracy in predicting the static joint angle as a function of input pressures is presented. Using this analytical model, we perform dynamic characterization of this system. Finally, we propose a sliding-mode controller, and a sliding mode controller augmented by a feed-forward term to modulate miniature solenoid valves that control air flow to each actuator. Experiments show that both controllers function well, while the feed-forward term improves the performance of the controller following dynamic trajectories.
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spelling pubmed-61935852018-11-05 Reverse pneumatic artificial muscles (rPAMs): Modeling, integration, and control Skorina, Erik H. Luo, Ming Oo, Wut Yee Tao, Weijia Chen, Fuchen Youssefian, Sina Rahbar, Nima Onal, Cagdas D. PLoS One Research Article Despite offering many advantages over traditional rigid actuators, soft pneumatic actuators suffer from a lack of comprehensive, computationally efficient models and precise embedded control schemes without bulky flow-control valves and extensive computer hardware. In this article, we consider an inexpensive and reliable soft linear actuator, called the reverse pneumatic artificial muscle (rPAM), which consists of silicone rubber that is radially constrained by symmetrical double-helix threading. We describe analytical and numerical static models of this actuator, and compare their performance against experimental results. To study the application of rPAMs to operate underlying kinematic linkage skeletons, we consider a single degree-of-freedom revolute joint that is driven antagonistically by two of these actuators. An analytical model is then derived, and its accuracy in predicting the static joint angle as a function of input pressures is presented. Using this analytical model, we perform dynamic characterization of this system. Finally, we propose a sliding-mode controller, and a sliding mode controller augmented by a feed-forward term to modulate miniature solenoid valves that control air flow to each actuator. Experiments show that both controllers function well, while the feed-forward term improves the performance of the controller following dynamic trajectories. Public Library of Science 2018-10-12 /pmc/articles/PMC6193585/ /pubmed/30312314 http://dx.doi.org/10.1371/journal.pone.0204637 Text en © 2018 Skorina et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Skorina, Erik H.
Luo, Ming
Oo, Wut Yee
Tao, Weijia
Chen, Fuchen
Youssefian, Sina
Rahbar, Nima
Onal, Cagdas D.
Reverse pneumatic artificial muscles (rPAMs): Modeling, integration, and control
title Reverse pneumatic artificial muscles (rPAMs): Modeling, integration, and control
title_full Reverse pneumatic artificial muscles (rPAMs): Modeling, integration, and control
title_fullStr Reverse pneumatic artificial muscles (rPAMs): Modeling, integration, and control
title_full_unstemmed Reverse pneumatic artificial muscles (rPAMs): Modeling, integration, and control
title_short Reverse pneumatic artificial muscles (rPAMs): Modeling, integration, and control
title_sort reverse pneumatic artificial muscles (rpams): modeling, integration, and control
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6193585/
https://www.ncbi.nlm.nih.gov/pubmed/30312314
http://dx.doi.org/10.1371/journal.pone.0204637
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