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Self-Sensing Control for Soft-Material Actuators Based on Dielectric Elastomers
Due to their energy density and softness that are comparable to human muscles dielectric elastomer (DE) transducers are well-suited for soft-robotic applications. This kind of transducer combines actuator and sensor functionality within one transducer so that no external senors to measure the deform...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7805669/ https://www.ncbi.nlm.nih.gov/pubmed/33501148 http://dx.doi.org/10.3389/frobt.2019.00133 |
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author | Hoffstadt, Thorben Maas, Jürgen |
author_facet | Hoffstadt, Thorben Maas, Jürgen |
author_sort | Hoffstadt, Thorben |
collection | PubMed |
description | Due to their energy density and softness that are comparable to human muscles dielectric elastomer (DE) transducers are well-suited for soft-robotic applications. This kind of transducer combines actuator and sensor functionality within one transducer so that no external senors to measure the deformation or to detect collisions are required. Within this contribution we present a novel self-sensing control for a DE stack-transducer that allows to control several different quantities of the DE transducer with the same controller. This flexibility is advantageous e.g., for the development of human machine interfaces with soft-bodied robots. After introducing the DE stack-transducer that is driven by a bidirectional flyback converter, the development of the self-sensing state and disturbance estimator based on an extended Kalman-filter is explained. Compared to known estimators designed for DE transducers supplied by bulky high-voltage amplifiers this one does not require any superimposed excitation to enable the sensor capability so that it also can be used with economic and competitive power electronics like the flyback converter. Due to the behavior of this converter a sliding mode energy controller is designed afterwards. By introducing different feed-forward controls the voltage, force or deformation can be controlled. The validation proofs that both the developed self-sensing estimator as well as the self-sensing control yield comparable results as previously published sensor-based approaches. |
format | Online Article Text |
id | pubmed-7805669 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-78056692021-01-25 Self-Sensing Control for Soft-Material Actuators Based on Dielectric Elastomers Hoffstadt, Thorben Maas, Jürgen Front Robot AI Robotics and AI Due to their energy density and softness that are comparable to human muscles dielectric elastomer (DE) transducers are well-suited for soft-robotic applications. This kind of transducer combines actuator and sensor functionality within one transducer so that no external senors to measure the deformation or to detect collisions are required. Within this contribution we present a novel self-sensing control for a DE stack-transducer that allows to control several different quantities of the DE transducer with the same controller. This flexibility is advantageous e.g., for the development of human machine interfaces with soft-bodied robots. After introducing the DE stack-transducer that is driven by a bidirectional flyback converter, the development of the self-sensing state and disturbance estimator based on an extended Kalman-filter is explained. Compared to known estimators designed for DE transducers supplied by bulky high-voltage amplifiers this one does not require any superimposed excitation to enable the sensor capability so that it also can be used with economic and competitive power electronics like the flyback converter. Due to the behavior of this converter a sliding mode energy controller is designed afterwards. By introducing different feed-forward controls the voltage, force or deformation can be controlled. The validation proofs that both the developed self-sensing estimator as well as the self-sensing control yield comparable results as previously published sensor-based approaches. Frontiers Media S.A. 2019-12-13 /pmc/articles/PMC7805669/ /pubmed/33501148 http://dx.doi.org/10.3389/frobt.2019.00133 Text en Copyright © 2019 Hoffstadt and Maas. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Robotics and AI Hoffstadt, Thorben Maas, Jürgen Self-Sensing Control for Soft-Material Actuators Based on Dielectric Elastomers |
title | Self-Sensing Control for Soft-Material Actuators Based on Dielectric Elastomers |
title_full | Self-Sensing Control for Soft-Material Actuators Based on Dielectric Elastomers |
title_fullStr | Self-Sensing Control for Soft-Material Actuators Based on Dielectric Elastomers |
title_full_unstemmed | Self-Sensing Control for Soft-Material Actuators Based on Dielectric Elastomers |
title_short | Self-Sensing Control for Soft-Material Actuators Based on Dielectric Elastomers |
title_sort | self-sensing control for soft-material actuators based on dielectric elastomers |
topic | Robotics and AI |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7805669/ https://www.ncbi.nlm.nih.gov/pubmed/33501148 http://dx.doi.org/10.3389/frobt.2019.00133 |
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