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Impedance Control for Robotic Rehabilitation: A Robust Markovian Approach
The human-robot interaction has played an important role in rehabilitation robotics and impedance control has been used in the regulation of interaction forces between the robot actuator and human limbs. Series elastic actuators (SEAs) have been an efficient solution in the design of this kind of ro...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5573722/ https://www.ncbi.nlm.nih.gov/pubmed/28883790 http://dx.doi.org/10.3389/fnbot.2017.00043 |
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author | Jutinico, Andres L. Jaimes, Jonathan C. Escalante, Felix M. Perez-Ibarra, Juan C. Terra, Marco H. Siqueira, Adriano A. G. |
author_facet | Jutinico, Andres L. Jaimes, Jonathan C. Escalante, Felix M. Perez-Ibarra, Juan C. Terra, Marco H. Siqueira, Adriano A. G. |
author_sort | Jutinico, Andres L. |
collection | PubMed |
description | The human-robot interaction has played an important role in rehabilitation robotics and impedance control has been used in the regulation of interaction forces between the robot actuator and human limbs. Series elastic actuators (SEAs) have been an efficient solution in the design of this kind of robotic application. Standard implementations of impedance control with SEAs require an internal force control loop for guaranteeing the desired impedance output. However, nonlinearities and uncertainties hamper such a guarantee of an accurate force level in this human-robot interaction. This paper addresses the dependence of the impedance control performance on the force control and proposes a control approach that improves the force control robustness. A unified model of the human-robot system that considers the ankle impedance by a second-order dynamics subject to uncertainties in the stiffness, damping, and inertia parameters has been developed. Fixed, resistive, and passive operation modes of the robotics system were defined, where transition probabilities among the modes were modeled through a Markov chain. A robust regulator for Markovian jump linear systems was used in the design of the force control. Experimental results show the approach improves the impedance control performance. For comparison purposes, a standard [Formula: see text] force controller based on the fixed operation mode has also been designed. The Markovian control approach outperformed the [Formula: see text] control when all operation modes were taken into account. |
format | Online Article Text |
id | pubmed-5573722 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-55737222017-09-07 Impedance Control for Robotic Rehabilitation: A Robust Markovian Approach Jutinico, Andres L. Jaimes, Jonathan C. Escalante, Felix M. Perez-Ibarra, Juan C. Terra, Marco H. Siqueira, Adriano A. G. Front Neurorobot Neuroscience The human-robot interaction has played an important role in rehabilitation robotics and impedance control has been used in the regulation of interaction forces between the robot actuator and human limbs. Series elastic actuators (SEAs) have been an efficient solution in the design of this kind of robotic application. Standard implementations of impedance control with SEAs require an internal force control loop for guaranteeing the desired impedance output. However, nonlinearities and uncertainties hamper such a guarantee of an accurate force level in this human-robot interaction. This paper addresses the dependence of the impedance control performance on the force control and proposes a control approach that improves the force control robustness. A unified model of the human-robot system that considers the ankle impedance by a second-order dynamics subject to uncertainties in the stiffness, damping, and inertia parameters has been developed. Fixed, resistive, and passive operation modes of the robotics system were defined, where transition probabilities among the modes were modeled through a Markov chain. A robust regulator for Markovian jump linear systems was used in the design of the force control. Experimental results show the approach improves the impedance control performance. For comparison purposes, a standard [Formula: see text] force controller based on the fixed operation mode has also been designed. The Markovian control approach outperformed the [Formula: see text] control when all operation modes were taken into account. Frontiers Media S.A. 2017-08-24 /pmc/articles/PMC5573722/ /pubmed/28883790 http://dx.doi.org/10.3389/fnbot.2017.00043 Text en Copyright © 2017 Jutinico, Jaimes, Escalante, Perez-Ibarra, Terra and Siqueira. 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) or licensor 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 | Neuroscience Jutinico, Andres L. Jaimes, Jonathan C. Escalante, Felix M. Perez-Ibarra, Juan C. Terra, Marco H. Siqueira, Adriano A. G. Impedance Control for Robotic Rehabilitation: A Robust Markovian Approach |
title | Impedance Control for Robotic Rehabilitation: A Robust Markovian Approach |
title_full | Impedance Control for Robotic Rehabilitation: A Robust Markovian Approach |
title_fullStr | Impedance Control for Robotic Rehabilitation: A Robust Markovian Approach |
title_full_unstemmed | Impedance Control for Robotic Rehabilitation: A Robust Markovian Approach |
title_short | Impedance Control for Robotic Rehabilitation: A Robust Markovian Approach |
title_sort | impedance control for robotic rehabilitation: a robust markovian approach |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5573722/ https://www.ncbi.nlm.nih.gov/pubmed/28883790 http://dx.doi.org/10.3389/fnbot.2017.00043 |
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