The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
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The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Le but de cette étude était de développer un contrôleur pratique de stimulation électrique fonctionnelle (FES) pour la restauration des mouvements articulaires basé sur une technique de contrôle optimale en mettant en cascade un contrôle prédictif de modèle linéaire (MPC) et une transformation non linéaire. La configuration en cascade visait à obtenir un contrôleur FES capable de gérer un système non linéaire. La transformation non linéaire a été utilisée pour transformer la solution linéaire du MPC linéaire en une solution non linéaire sous la forme d’une intensité de stimulation électrique optimisée. Quatre types différents de fonctions non linéaires ont été utilisés pour réaliser la transformation non linéaire. Une estimation simple des paramètres pour déterminer la valeur du paramètre de transformation non linéaire a également été développée. La capacité de contrôle de suivi du contrôleur proposé ainsi que l'estimation des paramètres ont été examinées lors du contrôle du mouvement de l'articulation du poignet 1-DOF par simulation informatique. Le contrôleur proposé a également été comparé à un contrôleur FES flou. Le contrôleur MPC-FES proposé avec la valeur estimée du paramètre fonctionnait correctement et avait une meilleure précision de contrôle que le contrôleur flou. Il a été suggéré que l'estimation des paramètres était utile et efficace dans les applications pratiques de contrôle FES afin de réduire le temps nécessaire à la détermination de la valeur du paramètre du contrôleur proposé.
Fauzan ARROFIQI
Tohoku University
Takashi WATANABE
Tohoku University
Achmad ARIFIN
Institut Teknologi Sepuluh Nopember (ITS)
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Fauzan ARROFIQI, Takashi WATANABE, Achmad ARIFIN, "A Computer Simulation Study on Movement Control by Functional Electrical Stimulation Using Optimal Control Technique with Simplified Parameter Estimation" in IEICE TRANSACTIONS on Information,
vol. E106-D, no. 5, pp. 1059-1068, May 2023, doi: 10.1587/transinf.2022EDP7093.
Abstract: The purpose of this study was to develop a practical functional electrical stimulation (FES) controller for joint movements restoration based on an optimal control technique by cascading a linear model predictive control (MPC) and a nonlinear transformation. The cascading configuration was aimed to obtain an FES controller that is able to deal with a nonlinear system. The nonlinear transformation was utilized to transform the linear solution of linear MPC to become a nonlinear solution in form of optimized electrical stimulation intensity. Four different types of nonlinear functions were used to realize the nonlinear transformation. A simple parameter estimation to determine the value of the nonlinear transformation parameter was also developed. The tracking control capability of the proposed controller along with the parameter estimation was examined in controlling the 1-DOF wrist joint movement through computer simulation. The proposed controller was also compared with a fuzzy FES controller. The proposed MPC-FES controller with estimated parameter value worked properly and had a better control accuracy than the fuzzy controller. The parameter estimation was suggested to be useful and effective in practical FES control applications to reduce the time-consuming of determining the parameter value of the proposed controller.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.2022EDP7093/_p
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@ARTICLE{e106-d_5_1059,
author={Fauzan ARROFIQI, Takashi WATANABE, Achmad ARIFIN, },
journal={IEICE TRANSACTIONS on Information},
title={A Computer Simulation Study on Movement Control by Functional Electrical Stimulation Using Optimal Control Technique with Simplified Parameter Estimation},
year={2023},
volume={E106-D},
number={5},
pages={1059-1068},
abstract={The purpose of this study was to develop a practical functional electrical stimulation (FES) controller for joint movements restoration based on an optimal control technique by cascading a linear model predictive control (MPC) and a nonlinear transformation. The cascading configuration was aimed to obtain an FES controller that is able to deal with a nonlinear system. The nonlinear transformation was utilized to transform the linear solution of linear MPC to become a nonlinear solution in form of optimized electrical stimulation intensity. Four different types of nonlinear functions were used to realize the nonlinear transformation. A simple parameter estimation to determine the value of the nonlinear transformation parameter was also developed. The tracking control capability of the proposed controller along with the parameter estimation was examined in controlling the 1-DOF wrist joint movement through computer simulation. The proposed controller was also compared with a fuzzy FES controller. The proposed MPC-FES controller with estimated parameter value worked properly and had a better control accuracy than the fuzzy controller. The parameter estimation was suggested to be useful and effective in practical FES control applications to reduce the time-consuming of determining the parameter value of the proposed controller.},
keywords={},
doi={10.1587/transinf.2022EDP7093},
ISSN={1745-1361},
month={May},}
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TY - JOUR
TI - A Computer Simulation Study on Movement Control by Functional Electrical Stimulation Using Optimal Control Technique with Simplified Parameter Estimation
T2 - IEICE TRANSACTIONS on Information
SP - 1059
EP - 1068
AU - Fauzan ARROFIQI
AU - Takashi WATANABE
AU - Achmad ARIFIN
PY - 2023
DO - 10.1587/transinf.2022EDP7093
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E106-D
IS - 5
JA - IEICE TRANSACTIONS on Information
Y1 - May 2023
AB - The purpose of this study was to develop a practical functional electrical stimulation (FES) controller for joint movements restoration based on an optimal control technique by cascading a linear model predictive control (MPC) and a nonlinear transformation. The cascading configuration was aimed to obtain an FES controller that is able to deal with a nonlinear system. The nonlinear transformation was utilized to transform the linear solution of linear MPC to become a nonlinear solution in form of optimized electrical stimulation intensity. Four different types of nonlinear functions were used to realize the nonlinear transformation. A simple parameter estimation to determine the value of the nonlinear transformation parameter was also developed. The tracking control capability of the proposed controller along with the parameter estimation was examined in controlling the 1-DOF wrist joint movement through computer simulation. The proposed controller was also compared with a fuzzy FES controller. The proposed MPC-FES controller with estimated parameter value worked properly and had a better control accuracy than the fuzzy controller. The parameter estimation was suggested to be useful and effective in practical FES control applications to reduce the time-consuming of determining the parameter value of the proposed controller.
ER -