Forward and inverse predictive model for the trajectory tracking control of a lower limb exoskeleton for gait rehabilitation: simulation modelling analysis

The movement of a lower limb exoskeleton requires a reasonably accurate control method to allow for an effective gait therapy session to transpire. Trajectory tracking is a nontrivial means of passive rehabilitation technique to correct the motion of the patients' impaired limb. This paper prop...

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Main Authors: Muhammad Aizzat, Zakaria, Anwar, P. P. Abdul Majeed, Zahari, Taha, M. M., Alim, Baarath, K.
Format: Conference or Workshop Item
Language:English
Published: Institute of Physics Publishing 2018
Subjects:
Online Access:http://umpir.ump.edu.my/id/eprint/23591/
http://umpir.ump.edu.my/id/eprint/23591/
http://umpir.ump.edu.my/id/eprint/23591/1/Forward%20and%20inverse%20predictive%20model%20for%20the%20trajectory%20tracking%20control%20of%20a%20lower%20limb%20exoskeleton%20for%20gait%20rehabilitation.pdf
id ump-23591
recordtype eprints
spelling ump-235912019-05-16T06:48:28Z http://umpir.ump.edu.my/id/eprint/23591/ Forward and inverse predictive model for the trajectory tracking control of a lower limb exoskeleton for gait rehabilitation: simulation modelling analysis Muhammad Aizzat, Zakaria Anwar, P. P. Abdul Majeed Zahari, Taha M. M., Alim Baarath, K. TS Manufactures The movement of a lower limb exoskeleton requires a reasonably accurate control method to allow for an effective gait therapy session to transpire. Trajectory tracking is a nontrivial means of passive rehabilitation technique to correct the motion of the patients' impaired limb. This paper proposes an inverse predictive model that is coupled together with the forward kinematics of the exoskeleton to estimate the behaviour of the system. A conventional PID control system is used to converge the required joint angles based on the desired input from the inverse predictive model. It was demonstrated through the present study, that the inverse predictive model is capable of meeting the trajectory demand with acceptable error tolerance. The findings further suggest the ability of the predictive model of the exoskeleton to predict a correct joint angle command to the system. Institute of Physics Publishing 2018-03 Conference or Workshop Item PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/23591/1/Forward%20and%20inverse%20predictive%20model%20for%20the%20trajectory%20tracking%20control%20of%20a%20lower%20limb%20exoskeleton%20for%20gait%20rehabilitation.pdf Muhammad Aizzat, Zakaria and Anwar, P. P. Abdul Majeed and Zahari, Taha and M. M., Alim and Baarath, K. (2018) Forward and inverse predictive model for the trajectory tracking control of a lower limb exoskeleton for gait rehabilitation: simulation modelling analysis. In: 4th Asia Pacific Conference on Manufacturing Systems and the 3rd International Manufacturing Engineering Conference, APCOMS-iMEC 2017, 7-8 December 2017 , Yogyakarta, Indonesia. pp. 1-6., 319 (1). ISSN 1757-8981 (Print); 1757-899X (Online) https://iopscience.iop.org/article/10.1088/1757-899X/319/1/012052/pdf
repository_type Digital Repository
institution_category Local University
institution Universiti Malaysia Pahang
building UMP Institutional Repository
collection Online Access
language English
topic TS Manufactures
spellingShingle TS Manufactures
Muhammad Aizzat, Zakaria
Anwar, P. P. Abdul Majeed
Zahari, Taha
M. M., Alim
Baarath, K.
Forward and inverse predictive model for the trajectory tracking control of a lower limb exoskeleton for gait rehabilitation: simulation modelling analysis
description The movement of a lower limb exoskeleton requires a reasonably accurate control method to allow for an effective gait therapy session to transpire. Trajectory tracking is a nontrivial means of passive rehabilitation technique to correct the motion of the patients' impaired limb. This paper proposes an inverse predictive model that is coupled together with the forward kinematics of the exoskeleton to estimate the behaviour of the system. A conventional PID control system is used to converge the required joint angles based on the desired input from the inverse predictive model. It was demonstrated through the present study, that the inverse predictive model is capable of meeting the trajectory demand with acceptable error tolerance. The findings further suggest the ability of the predictive model of the exoskeleton to predict a correct joint angle command to the system.
format Conference or Workshop Item
author Muhammad Aizzat, Zakaria
Anwar, P. P. Abdul Majeed
Zahari, Taha
M. M., Alim
Baarath, K.
author_facet Muhammad Aizzat, Zakaria
Anwar, P. P. Abdul Majeed
Zahari, Taha
M. M., Alim
Baarath, K.
author_sort Muhammad Aizzat, Zakaria
title Forward and inverse predictive model for the trajectory tracking control of a lower limb exoskeleton for gait rehabilitation: simulation modelling analysis
title_short Forward and inverse predictive model for the trajectory tracking control of a lower limb exoskeleton for gait rehabilitation: simulation modelling analysis
title_full Forward and inverse predictive model for the trajectory tracking control of a lower limb exoskeleton for gait rehabilitation: simulation modelling analysis
title_fullStr Forward and inverse predictive model for the trajectory tracking control of a lower limb exoskeleton for gait rehabilitation: simulation modelling analysis
title_full_unstemmed Forward and inverse predictive model for the trajectory tracking control of a lower limb exoskeleton for gait rehabilitation: simulation modelling analysis
title_sort forward and inverse predictive model for the trajectory tracking control of a lower limb exoskeleton for gait rehabilitation: simulation modelling analysis
publisher Institute of Physics Publishing
publishDate 2018
url http://umpir.ump.edu.my/id/eprint/23591/
http://umpir.ump.edu.my/id/eprint/23591/
http://umpir.ump.edu.my/id/eprint/23591/1/Forward%20and%20inverse%20predictive%20model%20for%20the%20trajectory%20tracking%20control%20of%20a%20lower%20limb%20exoskeleton%20for%20gait%20rehabilitation.pdf
first_indexed 2023-09-18T22:35:24Z
last_indexed 2023-09-18T22:35:24Z
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