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Simulation Evaluation for Methods Used to Determine Muscular Internal Force Based on Joint Stiffness Using Muscular Internal Force Feedforward Controller for Musculoskeletal System

This study proposes two novel methods for determining the muscular internal force (MIF) based on joint stiffness, using an MIF feedforward controller for the musculoskeletal system. The controller was developed in a previous study, where we found that it could be applied to achieve any desired end-p...

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Autores principales: Matsutani, Yuki, Tahara, Kenji, Kino, Hitoshi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8502805/
https://www.ncbi.nlm.nih.gov/pubmed/34646865
http://dx.doi.org/10.3389/frobt.2021.699792
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author Matsutani, Yuki
Tahara, Kenji
Kino, Hitoshi
author_facet Matsutani, Yuki
Tahara, Kenji
Kino, Hitoshi
author_sort Matsutani, Yuki
collection PubMed
description This study proposes two novel methods for determining the muscular internal force (MIF) based on joint stiffness, using an MIF feedforward controller for the musculoskeletal system. The controller was developed in a previous study, where we found that it could be applied to achieve any desired end-point position without the use of sensors, by providing the MIF as a feedforward input to individual muscles. However, achieving motion with good response and low stiffness using the system, posed a challenge. Furthermore, the controller was subject to an ill-posed problem, where the input could not be uniquely determined. We propose two methods to improve the control performance of this controller. The first method involves determining a MIF that can independently control the response and stiffness at a desired position, and the second method involves the definition of an arbitrary vector that describes the stiffnesses at the initial and desired positions to uniquely determine the MIF balance at each position. The numerical simulation results reported in this study demonstrate the effectiveness of both proposed methods.
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spelling pubmed-85028052021-10-12 Simulation Evaluation for Methods Used to Determine Muscular Internal Force Based on Joint Stiffness Using Muscular Internal Force Feedforward Controller for Musculoskeletal System Matsutani, Yuki Tahara, Kenji Kino, Hitoshi Front Robot AI Robotics and AI This study proposes two novel methods for determining the muscular internal force (MIF) based on joint stiffness, using an MIF feedforward controller for the musculoskeletal system. The controller was developed in a previous study, where we found that it could be applied to achieve any desired end-point position without the use of sensors, by providing the MIF as a feedforward input to individual muscles. However, achieving motion with good response and low stiffness using the system, posed a challenge. Furthermore, the controller was subject to an ill-posed problem, where the input could not be uniquely determined. We propose two methods to improve the control performance of this controller. The first method involves determining a MIF that can independently control the response and stiffness at a desired position, and the second method involves the definition of an arbitrary vector that describes the stiffnesses at the initial and desired positions to uniquely determine the MIF balance at each position. The numerical simulation results reported in this study demonstrate the effectiveness of both proposed methods. Frontiers Media S.A. 2021-09-27 /pmc/articles/PMC8502805/ /pubmed/34646865 http://dx.doi.org/10.3389/frobt.2021.699792 Text en Copyright © 2021 Matsutani, Tahara and Kino. https://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
Matsutani, Yuki
Tahara, Kenji
Kino, Hitoshi
Simulation Evaluation for Methods Used to Determine Muscular Internal Force Based on Joint Stiffness Using Muscular Internal Force Feedforward Controller for Musculoskeletal System
title Simulation Evaluation for Methods Used to Determine Muscular Internal Force Based on Joint Stiffness Using Muscular Internal Force Feedforward Controller for Musculoskeletal System
title_full Simulation Evaluation for Methods Used to Determine Muscular Internal Force Based on Joint Stiffness Using Muscular Internal Force Feedforward Controller for Musculoskeletal System
title_fullStr Simulation Evaluation for Methods Used to Determine Muscular Internal Force Based on Joint Stiffness Using Muscular Internal Force Feedforward Controller for Musculoskeletal System
title_full_unstemmed Simulation Evaluation for Methods Used to Determine Muscular Internal Force Based on Joint Stiffness Using Muscular Internal Force Feedforward Controller for Musculoskeletal System
title_short Simulation Evaluation for Methods Used to Determine Muscular Internal Force Based on Joint Stiffness Using Muscular Internal Force Feedforward Controller for Musculoskeletal System
title_sort simulation evaluation for methods used to determine muscular internal force based on joint stiffness using muscular internal force feedforward controller for musculoskeletal system
topic Robotics and AI
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8502805/
https://www.ncbi.nlm.nih.gov/pubmed/34646865
http://dx.doi.org/10.3389/frobt.2021.699792
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