Design and implemtation of a real-time adaptive learning algorithm controller for a 3-DOF parallel manipulator / Mustafa Jabbar Hayyawi

Design and implemtation of a real-time adaptive learning algorithm controller for a 3-DOF parallel manipulator / Mustafa Jabbar Hayyawi

A parallel manipulator is a closed loop mechanism which consists of a moving platform that is connected to a fixed base by at least two kinematic chains in parallel. Parallel manipulators can provide several advantages, such as high stiffness, high accuracy, and low inertia but also have some disadv...

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Main Author: Jabbar Hayyawi, Mustafa
Format: Student Project
Language:English
Published: Institute of Graduate Studies, UiTM 2016
Subjects:
Malaysia
Online Access:http://ir.uitm.edu.my/id/eprint/19642/
http://ir.uitm.edu.my/id/eprint/19642/1/ABS_MUSTAFA%20JABBAR%20HAYYAWI%20TDRA%20VOL%209%20IGS%2016.pdf
id uitm-19642
recordtype eprints
spelling uitm-196422018-06-07T04:11:18Z http://ir.uitm.edu.my/id/eprint/19642/ Design and implemtation of a real-time adaptive learning algorithm controller for a 3-DOF parallel manipulator / Mustafa Jabbar Hayyawi Jabbar Hayyawi, Mustafa Malaysia A parallel manipulator is a closed loop mechanism which consists of a moving platform that is connected to a fixed base by at least two kinematic chains in parallel. Parallel manipulators can provide several advantages, such as high stiffness, high accuracy, and low inertia but also have some disadvantages, such as small workspace, complicated structures, a high cost, and also pose a major challenge to their analysis and control. To overcome the above shortcomings, progress on the development of parallel manipulators with less than 6-DOF has been accelerated. In this thesis, a new parallel manipulator with three degrees of freedom DOF is designed. Kinematic of the manipulator including inverse kinematic, Jacobian matrix and velocity equation are analyzed. Performance indices such as workspace, dexterity and stiffness, of the parallel manipulator are studied. The parallel manipulator is optimized based on the performance indices to obtain on the optimal design parameters for achieved maximum performance of the parallel manipulator. A prototype was fabricated to demonstrate the manipulator. An electronic board, transistor relay driver circuit, is designed for the purpose of establishing communication interface between the computer, adaptive learning algorithm and the actuator mechanism. Design and development an adaptive learning algorithm controller ALAC of position the actuators is presented in real time parallel manipulator based on artificial neural network ANN… Institute of Graduate Studies, UiTM 2016 Student Project PeerReviewed text en http://ir.uitm.edu.my/id/eprint/19642/1/ABS_MUSTAFA%20JABBAR%20HAYYAWI%20TDRA%20VOL%209%20IGS%2016.pdf Jabbar Hayyawi, Mustafa (2016) Design and implemtation of a real-time adaptive learning algorithm controller for a 3-DOF parallel manipulator / Mustafa Jabbar Hayyawi. [Student Project]
repository_type Digital Repository
institution_category Local University
institution Universiti Teknologi MARA
building UiTM Institutional Repository
collection Online Access
language English
topic Malaysia
spellingShingle Malaysia
Jabbar Hayyawi, Mustafa
Design and implemtation of a real-time adaptive learning algorithm controller for a 3-DOF parallel manipulator / Mustafa Jabbar Hayyawi
description A parallel manipulator is a closed loop mechanism which consists of a moving platform that is connected to a fixed base by at least two kinematic chains in parallel. Parallel manipulators can provide several advantages, such as high stiffness, high accuracy, and low inertia but also have some disadvantages, such as small workspace, complicated structures, a high cost, and also pose a major challenge to their analysis and control. To overcome the above shortcomings, progress on the development of parallel manipulators with less than 6-DOF has been accelerated. In this thesis, a new parallel manipulator with three degrees of freedom DOF is designed. Kinematic of the manipulator including inverse kinematic, Jacobian matrix and velocity equation are analyzed. Performance indices such as workspace, dexterity and stiffness, of the parallel manipulator are studied. The parallel manipulator is optimized based on the performance indices to obtain on the optimal design parameters for achieved maximum performance of the parallel manipulator. A prototype was fabricated to demonstrate the manipulator. An electronic board, transistor relay driver circuit, is designed for the purpose of establishing communication interface between the computer, adaptive learning algorithm and the actuator mechanism. Design and development an adaptive learning algorithm controller ALAC of position the actuators is presented in real time parallel manipulator based on artificial neural network ANN…
format Student Project
author Jabbar Hayyawi, Mustafa
author_facet Jabbar Hayyawi, Mustafa
author_sort Jabbar Hayyawi, Mustafa
title Design and implemtation of a real-time adaptive learning algorithm controller for a 3-DOF parallel manipulator / Mustafa Jabbar Hayyawi
title_short Design and implemtation of a real-time adaptive learning algorithm controller for a 3-DOF parallel manipulator / Mustafa Jabbar Hayyawi
title_full Design and implemtation of a real-time adaptive learning algorithm controller for a 3-DOF parallel manipulator / Mustafa Jabbar Hayyawi
title_fullStr Design and implemtation of a real-time adaptive learning algorithm controller for a 3-DOF parallel manipulator / Mustafa Jabbar Hayyawi
title_full_unstemmed Design and implemtation of a real-time adaptive learning algorithm controller for a 3-DOF parallel manipulator / Mustafa Jabbar Hayyawi
title_sort design and implemtation of a real-time adaptive learning algorithm controller for a 3-dof parallel manipulator / mustafa jabbar hayyawi
publisher Institute of Graduate Studies, UiTM
publishDate 2016
url http://ir.uitm.edu.my/id/eprint/19642/
http://ir.uitm.edu.my/id/eprint/19642/1/ABS_MUSTAFA%20JABBAR%20HAYYAWI%20TDRA%20VOL%209%20IGS%2016.pdf
first_indexed 2023-09-18T23:02:59Z
last_indexed 2023-09-18T23:02:59Z
_version_ 1777418297334038528

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