Exoskeleton Follow-Up Control Based on Parameter Optimization of Predictive Algorithm

The prediction of sensor data can help the exoskeleton control system to get the human motion intention and target position in advance, so as to reduce the human-machine interaction force. In this paper, an improved method for the prediction algorithm of exoskeleton sensor data is proposed. Through...

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Main Authors:	Shijia Zha, Tianyi Li, Lidan Cheng, Jihua Gu, Wei Wei, Xichuan Lin, Shaofei Gu
Format:	Article
Language:	English
Published:	Hindawi Limited 2021-01-01
Series:	Applied Bionics and Biomechanics
Online Access:	http://dx.doi.org/10.1155/2021/8850348

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spelling	doaj-805820b0d2f04a9a9a15a8330a7088252021-07-02T16:13:26ZengHindawi LimitedApplied Bionics and Biomechanics1176-23221754-21032021-01-01202110.1155/2021/88503488850348Exoskeleton Follow-Up Control Based on Parameter Optimization of Predictive AlgorithmShijia Zha0Tianyi Li1Lidan Cheng2Jihua Gu3Wei Wei4Xichuan Lin5Shaofei Gu6College of Optoelectronics Science and Engineering, Soochow University, Suzhou Jiangsu Province, 215000, ChinaCollege of Optoelectronics Science and Engineering, Soochow University, Suzhou Jiangsu Province, 215000, ChinaCollege of Optoelectronics Science and Engineering, Soochow University, Suzhou Jiangsu Province, 215000, ChinaCollege of Optoelectronics Science and Engineering, Soochow University, Suzhou Jiangsu Province, 215000, ChinaCollege of Optoelectronics Science and Engineering, Soochow University, Suzhou Jiangsu Province, 215000, ChinaMicro-Nano Automation Institute, Jiangsu Industrial Technology Research Institute, Suzhou, Jiangsu Province 215131, ChinaShanghai Huangpu District Fire Rescue Detachment, Shanghai 200001, ChinaThe prediction of sensor data can help the exoskeleton control system to get the human motion intention and target position in advance, so as to reduce the human-machine interaction force. In this paper, an improved method for the prediction algorithm of exoskeleton sensor data is proposed. Through an algorithm simulation test and two-link simulation experiment, the algorithm improves the prediction accuracy by 14.23 ± 0.5%, and the sensor data is smooth. Input the predicted signal into the two-link model, and use the calculated torque method to verify the prediction accuracy data and smoothness. The simulation results showed that the algorithm can predict the joint angle of the human body and can be used for the follow-up control of the swinging legs of the exoskeleton.http://dx.doi.org/10.1155/2021/8850348
collection	DOAJ
language	English
format	Article
sources	DOAJ
author	Shijia Zha Tianyi Li Lidan Cheng Jihua Gu Wei Wei Xichuan Lin Shaofei Gu
spellingShingle	Shijia Zha Tianyi Li Lidan Cheng Jihua Gu Wei Wei Xichuan Lin Shaofei Gu Exoskeleton Follow-Up Control Based on Parameter Optimization of Predictive Algorithm Applied Bionics and Biomechanics
author_facet	Shijia Zha Tianyi Li Lidan Cheng Jihua Gu Wei Wei Xichuan Lin Shaofei Gu
author_sort	Shijia Zha
title	Exoskeleton Follow-Up Control Based on Parameter Optimization of Predictive Algorithm
title_short	Exoskeleton Follow-Up Control Based on Parameter Optimization of Predictive Algorithm
title_full	Exoskeleton Follow-Up Control Based on Parameter Optimization of Predictive Algorithm
title_fullStr	Exoskeleton Follow-Up Control Based on Parameter Optimization of Predictive Algorithm
title_full_unstemmed	Exoskeleton Follow-Up Control Based on Parameter Optimization of Predictive Algorithm
title_sort	exoskeleton follow-up control based on parameter optimization of predictive algorithm
publisher	Hindawi Limited
series	Applied Bionics and Biomechanics
issn	1176-2322 1754-2103
publishDate	2021-01-01
description	The prediction of sensor data can help the exoskeleton control system to get the human motion intention and target position in advance, so as to reduce the human-machine interaction force. In this paper, an improved method for the prediction algorithm of exoskeleton sensor data is proposed. Through an algorithm simulation test and two-link simulation experiment, the algorithm improves the prediction accuracy by 14.23 ± 0.5%, and the sensor data is smooth. Input the predicted signal into the two-link model, and use the calculated torque method to verify the prediction accuracy data and smoothness. The simulation results showed that the algorithm can predict the joint angle of the human body and can be used for the follow-up control of the swinging legs of the exoskeleton.
url	http://dx.doi.org/10.1155/2021/8850348
work_keys_str_mv	AT shijiazha exoskeletonfollowupcontrolbasedonparameteroptimizationofpredictivealgorithm AT tianyili exoskeletonfollowupcontrolbasedonparameteroptimizationofpredictivealgorithm AT lidancheng exoskeletonfollowupcontrolbasedonparameteroptimizationofpredictivealgorithm AT jihuagu exoskeletonfollowupcontrolbasedonparameteroptimizationofpredictivealgorithm AT weiwei exoskeletonfollowupcontrolbasedonparameteroptimizationofpredictivealgorithm AT xichuanlin exoskeletonfollowupcontrolbasedonparameteroptimizationofpredictivealgorithm AT shaofeigu exoskeletonfollowupcontrolbasedonparameteroptimizationofpredictivealgorithm
_version_	1721326912208371712

Exoskeleton Follow-Up Control Based on Parameter Optimization of Predictive Algorithm

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