Intelligent trajectory conversion and inverse dynamic control of a 3-DOF neuro-rehabilitation platform

Tracking a desired trajectory in joint space has been favored in several robot manipulators and end-effector control scheme due to the simplicity and high sampling rate offered by the joint space scheme. This usually require the trajectory conversion process, of the desired position, velo...

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Main Authors:	Sado, Fatai, Sidek, Shahrul Na'im, Md. Yusof, Hazlina
Format:	Conference or Workshop Item
Language:	English English
Published:	IEEE 2015
Subjects:	TA168 Systems engineering
Online Access:	http://irep.iium.edu.my/43671/ http://irep.iium.edu.my/43671/ http://irep.iium.edu.my/43671/ http://irep.iium.edu.my/43671/4/43671-Intelligent_trajectory_conversion_and_inverse_dynamic_control_of_a_3-DOF_neuro-rehabilitation_platform_Fullarticle.pdf http://irep.iium.edu.my/43671/7/ASCC-organizer.pdf

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recordtype	eprints
spelling	iium-436712019-01-10T04:59:45Z http://irep.iium.edu.my/43671/ Intelligent trajectory conversion and inverse dynamic control of a 3-DOF neuro-rehabilitation platform Sado, Fatai Sidek, Shahrul Na'im Md. Yusof, Hazlina TA168 Systems engineering Tracking a desired trajectory in joint space has been favored in several robot manipulators and end-effector control scheme due to the simplicity and high sampling rate offered by the joint space scheme. This usually require the trajectory conversion process, of the desired position, velocity, and acceleration, from Cartesian space to joint space using conventional inverse kinematics solutions which have been known to have several limitations and which often pose a big challenge, computationally, and even prohibitive, to achieve, for some robot designs. In this study, an intelligent approach to the inverse kinematics problem using adaptive neuro-fuzzy inference system (ANFIS) is proposed for control of a 3-DOF end-effector based neurorehabilitation platform. The joint positions, velocities, and accelerations are achieved/predicted by means of the ANFIS networks which is trained with data obtained from the forward kinematics, velocity Jacobian and the differential of the velocity kinematics equations. Simulation studies have shown that the proposed intelligent techniques has simplified both the trajectory conversion process and the control framework while tracking is achieve to a high degree of accuracy. IEEE 2015 Conference or Workshop Item PeerReviewed application/pdf en http://irep.iium.edu.my/43671/4/43671-Intelligent_trajectory_conversion_and_inverse_dynamic_control_of_a_3-DOF_neuro-rehabilitation_platform_Fullarticle.pdf application/pdf en http://irep.iium.edu.my/43671/7/ASCC-organizer.pdf Sado, Fatai and Sidek, Shahrul Na'im and Md. Yusof, Hazlina (2015) Intelligent trajectory conversion and inverse dynamic control of a 3-DOF neuro-rehabilitation platform. In: 2015 10th Asian Control Conference (ASCC 2015), 31st May- 3rd June 2015, Kota Kinabalu, Sabah. http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7244421&punumber%3D7209153%26filter%3DAND(p_IS_Number%3A7244373)%26pageNumber%3D2 10.1109/ASCC.2015.7244421
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English English
topic	TA168 Systems engineering
spellingShingle	TA168 Systems engineering Sado, Fatai Sidek, Shahrul Na'im Md. Yusof, Hazlina Intelligent trajectory conversion and inverse dynamic control of a 3-DOF neuro-rehabilitation platform
description	Tracking a desired trajectory in joint space has been favored in several robot manipulators and end-effector control scheme due to the simplicity and high sampling rate offered by the joint space scheme. This usually require the trajectory conversion process, of the desired position, velocity, and acceleration, from Cartesian space to joint space using conventional inverse kinematics solutions which have been known to have several limitations and which often pose a big challenge, computationally, and even prohibitive, to achieve, for some robot designs. In this study, an intelligent approach to the inverse kinematics problem using adaptive neuro-fuzzy inference system (ANFIS) is proposed for control of a 3-DOF end-effector based neurorehabilitation platform. The joint positions, velocities, and accelerations are achieved/predicted by means of the ANFIS networks which is trained with data obtained from the forward kinematics, velocity Jacobian and the differential of the velocity kinematics equations. Simulation studies have shown that the proposed intelligent techniques has simplified both the trajectory conversion process and the control framework while tracking is achieve to a high degree of accuracy.
format	Conference or Workshop Item
author	Sado, Fatai Sidek, Shahrul Na'im Md. Yusof, Hazlina
author_facet	Sado, Fatai Sidek, Shahrul Na'im Md. Yusof, Hazlina
author_sort	Sado, Fatai
title	Intelligent trajectory conversion and inverse dynamic control of a 3-DOF neuro-rehabilitation platform
title_short	Intelligent trajectory conversion and inverse dynamic control of a 3-DOF neuro-rehabilitation platform
title_full	Intelligent trajectory conversion and inverse dynamic control of a 3-DOF neuro-rehabilitation platform
title_fullStr	Intelligent trajectory conversion and inverse dynamic control of a 3-DOF neuro-rehabilitation platform
title_full_unstemmed	Intelligent trajectory conversion and inverse dynamic control of a 3-DOF neuro-rehabilitation platform
title_sort	intelligent trajectory conversion and inverse dynamic control of a 3-dof neuro-rehabilitation platform
publisher	IEEE
publishDate	2015
url	http://irep.iium.edu.my/43671/ http://irep.iium.edu.my/43671/ http://irep.iium.edu.my/43671/ http://irep.iium.edu.my/43671/4/43671-Intelligent_trajectory_conversion_and_inverse_dynamic_control_of_a_3-DOF_neuro-rehabilitation_platform_Fullarticle.pdf http://irep.iium.edu.my/43671/7/ASCC-organizer.pdf
first_indexed	2023-09-18T21:02:10Z
last_indexed	2023-09-18T21:02:10Z
_version_	1777410696111194112

Intelligent trajectory conversion and inverse dynamic control of a 3-DOF neuro-rehabilitation platform

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