Multivariate control of robot using neural networks
66 p.
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Format: | Thesis |
Published: |
2011
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Online Access: | http://hdl.handle.net/10356/46978 |
_version_ | 1811680423760101376 |
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author | Chen, Wei |
author2 | Song Qing |
author_facet | Song Qing Chen, Wei |
author_sort | Chen, Wei |
collection | NTU |
description | 66 p. |
first_indexed | 2024-10-01T03:24:49Z |
format | Thesis |
id | ntu-10356/46978 |
institution | Nanyang Technological University |
last_indexed | 2024-10-01T03:24:49Z |
publishDate | 2011 |
record_format | dspace |
spelling | ntu-10356/469782023-07-04T16:28:30Z Multivariate control of robot using neural networks Chen, Wei Song Qing School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation::Control engineering 66 p. This thesis focuses on the study of the neural network (NN) and its application to robot multi-variable tracking control. A dynamic model of the robot manipulators was discussed. And the derivation of the dynamic equation of a realistic two degree-of-freedom (DOF) direct-drive manipulator will be introduced and finally a discrete-time model is obtained. Master of Science (Computer Control and Automation) 2011-12-27T05:51:30Z 2011-12-27T05:51:30Z 2009 2009 Thesis http://hdl.handle.net/10356/46978 Nanyang Technological University application/pdf |
spellingShingle | DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation::Control engineering Chen, Wei Multivariate control of robot using neural networks |
title | Multivariate control of robot using neural networks |
title_full | Multivariate control of robot using neural networks |
title_fullStr | Multivariate control of robot using neural networks |
title_full_unstemmed | Multivariate control of robot using neural networks |
title_short | Multivariate control of robot using neural networks |
title_sort | multivariate control of robot using neural networks |
topic | DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation::Control engineering |
url | http://hdl.handle.net/10356/46978 |
work_keys_str_mv | AT chenwei multivariatecontrolofrobotusingneuralnetworks |