Smart torque control for overloaded motor using artificial intelligence approach

This project report presents a methodology for implementation of a rule-based fuzzy logic controller applied to an induction motor torque control. The designed Fuzzy Logic Controller’s performance is weighed against with that of a PI controller. The pros of the Fuzzy Logic Controllers (FLCs) o...

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Main Author:	Mohamed, Hazizul
Format:	Thesis
Language:	English English English
Published:	2013
Subjects:	TK Electrical engineering Electronics Nuclear engineering
Online Access:	http://eprints.uthm.edu.my/1915/1/24p%20HAZIZUL%20MOHAMED.pdf http://eprints.uthm.edu.my/1915/2/HAZIZUL%20MOHAMED%20COPYRIGHT%20DECLARATION.pdf http://eprints.uthm.edu.my/1915/3/HAZIZUL%20MOHAMED%20WATERMARK.pdf
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id	my-uthm-ep.1915
record_format	uketd_dc
spelling	my-uthm-ep.19152021-10-12T04:37:33Z Smart torque control for overloaded motor using artificial intelligence approach 2013-01 Mohamed, Hazizul TK Electrical engineering. Electronics Nuclear engineering TK2000-2891 Dynamoelectric machinery and auxiliaries. Including generators, motors, transformers This project report presents a methodology for implementation of a rule-based fuzzy logic controller applied to an induction motor torque control. The designed Fuzzy Logic Controller’s performance is weighed against with that of a PI controller. The pros of the Fuzzy Logic Controllers (FLCs) over the conventional controllers are they are economically advantageous to develop, a wider range of operating conditions can be covered using FLCs, and they are easier to adapt in terms of natural language. Another advantage is that, an initial approximate set of fuzzy rules can be impulsively refined by a self-organizing fuzzy controller. For torque control of the induction motor, a reference torque has been used and the control architecture includes some rules. These rules portray a nonchalant relationship between two inputs and an output, all of which are nothing but normalized voltages. These are the input torque error denoted by Error (e), the input derivative of torque error denoted by Change of error (Δe), and the output frequency denoted by Change of Control (ωsl). The errors are evaluated according to the rules in accordance to the defined member functions. The member functions and the rules have been defined using the FIS editor given in MATLAB. Based on the rules the surface view of the control has been recorded. The system has been simulated in MATLAB/SIMULINK® and the results have been attached. The results obtained by using a conventional PI controller and the designed Fuzzy Logic Controller has been studied and compared. 2013-01 Thesis http://eprints.uthm.edu.my/1915/ http://eprints.uthm.edu.my/1915/1/24p%20HAZIZUL%20MOHAMED.pdf text en public http://eprints.uthm.edu.my/1915/2/HAZIZUL%20MOHAMED%20COPYRIGHT%20DECLARATION.pdf text en staffonly http://eprints.uthm.edu.my/1915/3/HAZIZUL%20MOHAMED%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	TK Electrical engineering Electronics Nuclear engineering TK Electrical engineering Electronics Nuclear engineering
spellingShingle	TK Electrical engineering Electronics Nuclear engineering TK Electrical engineering Electronics Nuclear engineering Mohamed, Hazizul Smart torque control for overloaded motor using artificial intelligence approach
description	This project report presents a methodology for implementation of a rule-based fuzzy logic controller applied to an induction motor torque control. The designed Fuzzy Logic Controller’s performance is weighed against with that of a PI controller. The pros of the Fuzzy Logic Controllers (FLCs) over the conventional controllers are they are economically advantageous to develop, a wider range of operating conditions can be covered using FLCs, and they are easier to adapt in terms of natural language. Another advantage is that, an initial approximate set of fuzzy rules can be impulsively refined by a self-organizing fuzzy controller. For torque control of the induction motor, a reference torque has been used and the control architecture includes some rules. These rules portray a nonchalant relationship between two inputs and an output, all of which are nothing but normalized voltages. These are the input torque error denoted by Error (e), the input derivative of torque error denoted by Change of error (Δe), and the output frequency denoted by Change of Control (ωsl). The errors are evaluated according to the rules in accordance to the defined member functions. The member functions and the rules have been defined using the FIS editor given in MATLAB. Based on the rules the surface view of the control has been recorded. The system has been simulated in MATLAB/SIMULINK® and the results have been attached. The results obtained by using a conventional PI controller and the designed Fuzzy Logic Controller has been studied and compared.
format	Thesis
qualification_name	Master of Philosophy (M.Phil.)
qualification_level	Master's degree
author	Mohamed, Hazizul
author_facet	Mohamed, Hazizul
author_sort	Mohamed, Hazizul
title	Smart torque control for overloaded motor using artificial intelligence approach
title_short	Smart torque control for overloaded motor using artificial intelligence approach
title_full	Smart torque control for overloaded motor using artificial intelligence approach
title_fullStr	Smart torque control for overloaded motor using artificial intelligence approach
title_full_unstemmed	Smart torque control for overloaded motor using artificial intelligence approach
title_sort	smart torque control for overloaded motor using artificial intelligence approach
granting_institution	Universiti Tun Hussein Onn Malaysia
granting_department	Fakulti Kejuruteraan Elektrik dan Elektronik
publishDate	2013
url	http://eprints.uthm.edu.my/1915/1/24p%20HAZIZUL%20MOHAMED.pdf http://eprints.uthm.edu.my/1915/2/HAZIZUL%20MOHAMED%20COPYRIGHT%20DECLARATION.pdf http://eprints.uthm.edu.my/1915/3/HAZIZUL%20MOHAMED%20WATERMARK.pdf
_version_	1747830881392787456

Smart torque control for overloaded motor using artificial intelligence approach

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