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Tracking Control of Parallel Robot Manipulators Using RBF Neural Network

Since parallel robots are the multibody systems with closed-loop structures, their movement equations usually are in the complex form of redundant coordinates and their dynamics parameters are usually uncertain. The aim of this paper is to improve the control quality for the parallel robot by applyi...

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Main Authors: Vu Le Huy, Nguyen Dinh Dzung
Format: Article
Language:English
Published: SpringerLink 2021
Subjects:
Parallel robot
Sliding mode control
Online Access:https://link.springer.com/chapter/10.1007/978-981-15-7527-3_59
https://dlib.phenikaa-uni.edu.vn/handle/PNK/2686
https://link.springer.com/chapter/10.1007/978-981-15-7527-3_59
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spelling oai:localhost:PNK-26862022-08-17T05:54:48Z Tracking Control of Parallel Robot Manipulators Using RBF Neural Network Vu Le Huy Nguyen Dinh Dzung Parallel robot Sliding mode control Since parallel robots are the multibody systems with closed-loop structures, their movement equations usually are in the complex form of redundant coordinates and their dynamics parameters are usually uncertain. The aim of this paper is to improve the control quality for the parallel robot by applying RBF neutron network. Firstly, the movement equations of Rostock Delta robot are established as differential–algebraic systems of equations with redundant generalized coordinates. Then, the stableness of the control method based on sliding mode control law using neural network is proved. Finally, the error in tracking control of a specific Rostock Delta robot is simulated by using this method. 2021-09-09T10:36:53Z 2021-09-09T10:36:53Z 2021 Article https://link.springer.com/chapter/10.1007/978-981-15-7527-3_59 https://dlib.phenikaa-uni.edu.vn/handle/PNK/2686 https://link.springer.com/chapter/10.1007/978-981-15-7527-3_59 10.1007/978-981-15-7527-3_59 en SpringerLink
institution Digital Phenikaa
collection Digital Phenikaa
language English
topic Parallel robot
Sliding mode control
spellingShingle Parallel robot
Sliding mode control
Vu Le Huy
Nguyen Dinh Dzung
Tracking Control of Parallel Robot Manipulators Using RBF Neural Network
description Since parallel robots are the multibody systems with closed-loop structures, their movement equations usually are in the complex form of redundant coordinates and their dynamics parameters are usually uncertain. The aim of this paper is to improve the control quality for the parallel robot by applying RBF neutron network. Firstly, the movement equations of Rostock Delta robot are established as differential–algebraic systems of equations with redundant generalized coordinates. Then, the stableness of the control method based on sliding mode control law using neural network is proved. Finally, the error in tracking control of a specific Rostock Delta robot is simulated by using this method.
format Article
author Vu Le Huy
Nguyen Dinh Dzung
author_facet Vu Le Huy
Nguyen Dinh Dzung
author_sort Vu Le Huy
title Tracking Control of Parallel Robot Manipulators Using RBF Neural Network
title_short Tracking Control of Parallel Robot Manipulators Using RBF Neural Network
title_full Tracking Control of Parallel Robot Manipulators Using RBF Neural Network
title_fullStr Tracking Control of Parallel Robot Manipulators Using RBF Neural Network
title_full_unstemmed Tracking Control of Parallel Robot Manipulators Using RBF Neural Network
title_sort tracking control of parallel robot manipulators using rbf neural network
publisher SpringerLink
publishDate 2021
url https://link.springer.com/chapter/10.1007/978-981-15-7527-3_59
https://dlib.phenikaa-uni.edu.vn/handle/PNK/2686
https://link.springer.com/chapter/10.1007/978-981-15-7527-3_59
_version_ 1751856261341642752
score 8.881002

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