Gains self-tuning of a large compliance system by combining artificial neural networks and genetic algorithms

This project used two kinds of techniques in the field of artificial intelligence, the artificial neural network and the genetic algorithms, to self-tune the gain of a large compliance system a nonlinear servo pneumatic cylinder system for continuous load positioning.

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Bibliographic Details
Main Author:	Yuan, Yuan.
Other Authors:	Sim, Siang Kok
Format:	Theses and Dissertations
Language:	English
Published:	2009
Subjects:	DRNTU::Engineering::Mechanical engineering DRNTU::Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence
Online Access:	http://hdl.handle.net/10356/19862
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Institution:	Nanyang Technological University
Language:	English

id	sg-ntu-dr.10356-19862
record_format	dspace
spelling	sg-ntu-dr.10356-198622023-03-11T17:06:35Z Gains self-tuning of a large compliance system by combining artificial neural networks and genetic algorithms Yuan, Yuan. Sim, Siang Kok School of Mechanical and Production Engineering DRNTU::Engineering::Mechanical engineering DRNTU::Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence This project used two kinds of techniques in the field of artificial intelligence, the artificial neural network and the genetic algorithms, to self-tune the gain of a large compliance system a nonlinear servo pneumatic cylinder system for continuous load positioning. Master of Engineering (MPE) 2009-12-14T06:59:01Z 2009-12-14T06:59:01Z 1998 1998 Thesis http://hdl.handle.net/10356/19862 en NANYANG TECHNOLOGICAL UNIVERSITY 174 p. application/pdf
institution	Nanyang Technological University
building	NTU Library
continent	Asia
country	Singapore Singapore
content_provider	NTU Library
collection	DR-NTU
language	English
topic	DRNTU::Engineering::Mechanical engineering DRNTU::Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence
spellingShingle	DRNTU::Engineering::Mechanical engineering DRNTU::Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence Yuan, Yuan. Gains self-tuning of a large compliance system by combining artificial neural networks and genetic algorithms
description	This project used two kinds of techniques in the field of artificial intelligence, the artificial neural network and the genetic algorithms, to self-tune the gain of a large compliance system a nonlinear servo pneumatic cylinder system for continuous load positioning.
author2	Sim, Siang Kok
author_facet	Sim, Siang Kok Yuan, Yuan.
format	Theses and Dissertations
author	Yuan, Yuan.
author_sort	Yuan, Yuan.
title	Gains self-tuning of a large compliance system by combining artificial neural networks and genetic algorithms
title_short	Gains self-tuning of a large compliance system by combining artificial neural networks and genetic algorithms
title_full	Gains self-tuning of a large compliance system by combining artificial neural networks and genetic algorithms
title_fullStr	Gains self-tuning of a large compliance system by combining artificial neural networks and genetic algorithms
title_full_unstemmed	Gains self-tuning of a large compliance system by combining artificial neural networks and genetic algorithms
title_sort	gains self-tuning of a large compliance system by combining artificial neural networks and genetic algorithms
publishDate	2009
url	http://hdl.handle.net/10356/19862
_version_	1761781910562930688

Gains self-tuning of a large compliance system by combining artificial neural networks and genetic algorithms

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