Computational intelligence method for optimal rotary design system

The application of computational intelligence techniques to the field of industrial robot control is discussed. The core ideas behind using computation, evolutionary computation and fuzzy logic techniques are presented, along with a selection of specific real-world applications. The practical...

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Main Author:	P.Saminathan, Kantan
Format:	Thesis
Language:	English English English
Published:	2008
Subjects:	QA Mathematics QA76 Computer software
Online Access:	http://eprints.uthm.edu.my/7334/1/24p%20KANTAN%20P.SAMINATHAN.pdf http://eprints.uthm.edu.my/7334/2/KANTAN%20P.SAMINATHAN%20COPYRIGHT%20DECLARATION.pdf http://eprints.uthm.edu.my/7334/3/KANTAN%20P.SAMINATHAN%20WATERMARK.pdf
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id	my-uthm-ep.7334
record_format	uketd_dc
spelling	my-uthm-ep.73342022-07-21T03:57:09Z Computational intelligence method for optimal rotary design system 2008-11 P.Saminathan, Kantan QA Mathematics QA76 Computer software The application of computational intelligence techniques to the field of industrial robot control is discussed. The core ideas behind using computation, evolutionary computation and fuzzy logic techniques are presented, along with a selection of specific real-world applications. The practical advantages and disadvantages relative to more traditional approaches are made clear. The objective of this project was to investigate and compare different algorithms for the calculation of velocity from position information. The best algorithm was applied to a small robot arm system which consists of a controller (PC software), analog-to-digital and digital-to-analog converter PC card, power amplifier, DC motor, gear train and external load. Generally in robotic systems a velocity calculation is difficult or impossible to implement because of noise. Here in the project, fuzzy logic will be used to filter the noise from the position data before calculating velocity. The purpose of this research is to design fuzzy logic feedback controller to position the rotational system with one flexible joint. The system produces oscillations that need to be dampen. Here the PD (without) controller, ON-OFF controller, Linear Quadratic Regulator controller (LQR) and Fuzzy Logic controller (sugeno method) are being used to solve the mentioned oscillatory problem. In order to control the overall Rotary Flexible Joint System, the Fuzzy Logic controller (FLC) is designed base upon the coefficients of the existing LQR controller. Comparison between four controllers was being made through simulation and experiment and the results showed that the fuzzy controller performed better than the other controllers. 2008-11 Thesis http://eprints.uthm.edu.my/7334/ http://eprints.uthm.edu.my/7334/1/24p%20KANTAN%20P.SAMINATHAN.pdf text en public http://eprints.uthm.edu.my/7334/2/KANTAN%20P.SAMINATHAN%20COPYRIGHT%20DECLARATION.pdf text en staffonly http://eprints.uthm.edu.my/7334/3/KANTAN%20P.SAMINATHAN%20WATERMARK.pdf text en validuser mphil masters Universiti Tun Hussein Onn Malaysia Fakulti Kejuruteraan Elektrik dan Elektronik
institution	Universiti Tun Hussein Onn Malaysia
collection	UTHM Institutional Repository
language	English English English
topic	QA Mathematics QA76 Computer software
spellingShingle	QA Mathematics QA76 Computer software P.Saminathan, Kantan Computational intelligence method for optimal rotary design system
description	The application of computational intelligence techniques to the field of industrial robot control is discussed. The core ideas behind using computation, evolutionary computation and fuzzy logic techniques are presented, along with a selection of specific real-world applications. The practical advantages and disadvantages relative to more traditional approaches are made clear. The objective of this project was to investigate and compare different algorithms for the calculation of velocity from position information. The best algorithm was applied to a small robot arm system which consists of a controller (PC software), analog-to-digital and digital-to-analog converter PC card, power amplifier, DC motor, gear train and external load. Generally in robotic systems a velocity calculation is difficult or impossible to implement because of noise. Here in the project, fuzzy logic will be used to filter the noise from the position data before calculating velocity. The purpose of this research is to design fuzzy logic feedback controller to position the rotational system with one flexible joint. The system produces oscillations that need to be dampen. Here the PD (without) controller, ON-OFF controller, Linear Quadratic Regulator controller (LQR) and Fuzzy Logic controller (sugeno method) are being used to solve the mentioned oscillatory problem. In order to control the overall Rotary Flexible Joint System, the Fuzzy Logic controller (FLC) is designed base upon the coefficients of the existing LQR controller. Comparison between four controllers was being made through simulation and experiment and the results showed that the fuzzy controller performed better than the other controllers.
format	Thesis
qualification_name	Master of Philosophy (M.Phil.)
qualification_level	Master's degree
author	P.Saminathan, Kantan
author_facet	P.Saminathan, Kantan
author_sort	P.Saminathan, Kantan
title	Computational intelligence method for optimal rotary design system
title_short	Computational intelligence method for optimal rotary design system
title_full	Computational intelligence method for optimal rotary design system
title_fullStr	Computational intelligence method for optimal rotary design system
title_full_unstemmed	Computational intelligence method for optimal rotary design system
title_sort	computational intelligence method for optimal rotary design system
granting_institution	Universiti Tun Hussein Onn Malaysia
granting_department	Fakulti Kejuruteraan Elektrik dan Elektronik
publishDate	2008
url	http://eprints.uthm.edu.my/7334/1/24p%20KANTAN%20P.SAMINATHAN.pdf http://eprints.uthm.edu.my/7334/2/KANTAN%20P.SAMINATHAN%20COPYRIGHT%20DECLARATION.pdf http://eprints.uthm.edu.my/7334/3/KANTAN%20P.SAMINATHAN%20WATERMARK.pdf
_version_	1747831133243965440

Computational intelligence method for optimal rotary design system

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