A development of self-tuning quantitative feedback theory

This paper presents a development of self-tuning Quantitative Feedback Theory (QFT) for a non linear system. QFT is one type of robust controller which deals with plant uncertainty. The performance of robust controller for any uncertain plant is guaranteed based on pre-defined specifications. M...

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Main Authors:	Mansor, Hasmah, Khan, Sheroz, Gunawan, Teddy Surya, Mohd Noor, Samsul Bahari
Format:	Conference or Workshop Item
Language:	English
Published:	IEEExplore 2012
Subjects:	T Technology (General) TA168 Systems engineering
Online Access:	http://irep.iium.edu.my/25642/ http://irep.iium.edu.my/25642/ http://irep.iium.edu.my/25642/ http://irep.iium.edu.my/25642/1/06271341on_IEEExplore.pdf

id	iium-25642
recordtype	eprints
spelling	iium-256422012-09-05T06:25:35Z http://irep.iium.edu.my/25642/ A development of self-tuning quantitative feedback theory Mansor, Hasmah Khan, Sheroz Gunawan, Teddy Surya Mohd Noor, Samsul Bahari T Technology (General) TA168 Systems engineering This paper presents a development of self-tuning Quantitative Feedback Theory (QFT) for a non linear system. QFT is one type of robust controller which deals with plant uncertainty. The performance of robust controller for any uncertain plant is guaranteed based on pre-defined specifications. Meanwhile, self-tuning controller is one type of adaptive controller which also meant to solve the same control problem, however for slower plant drift. By combining both adaptive and robust controllers, both robust and adaptive performance can be achieved. The proposed algorithm is tested on a chosen case study, grain dryer plant. Grain dryer is a non linear plant with uncertainty as the characteristics of the plant can be affected by environmental changes, manufacturing tolerance and input/output disturbance. Based on the results obtained from this case study, the superiority of the proposed self-tuning QFT has been proven. From the comparison test conducted between self-tuning and standard QFT-based controllers, the proposed method produced more desirable response in terms of faster settling time, less percentage of overshoot with reduced ringing, smaller control effort required and wider leverage of uncertainty range. IEEExplore 2012 Conference or Workshop Item PeerReviewed application/pdf en http://irep.iium.edu.my/25642/1/06271341on_IEEExplore.pdf Mansor, Hasmah and Khan, Sheroz and Gunawan, Teddy Surya and Mohd Noor, Samsul Bahari (2012) A development of self-tuning quantitative feedback theory. In: International Conference on Computer and Communication Engineering (ICCCE 2012), 3-5 July 2012, Seri Pacific Hotel Kuala Lumpur. http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6271341&tag=1 10.1109/ICCCE.2012.6271341
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English
topic	T Technology (General) TA168 Systems engineering
spellingShingle	T Technology (General) TA168 Systems engineering Mansor, Hasmah Khan, Sheroz Gunawan, Teddy Surya Mohd Noor, Samsul Bahari A development of self-tuning quantitative feedback theory
description	This paper presents a development of self-tuning Quantitative Feedback Theory (QFT) for a non linear system. QFT is one type of robust controller which deals with plant uncertainty. The performance of robust controller for any uncertain plant is guaranteed based on pre-defined specifications. Meanwhile, self-tuning controller is one type of adaptive controller which also meant to solve the same control problem, however for slower plant drift. By combining both adaptive and robust controllers, both robust and adaptive performance can be achieved. The proposed algorithm is tested on a chosen case study, grain dryer plant. Grain dryer is a non linear plant with uncertainty as the characteristics of the plant can be affected by environmental changes, manufacturing tolerance and input/output disturbance. Based on the results obtained from this case study, the superiority of the proposed self-tuning QFT has been proven. From the comparison test conducted between self-tuning and standard QFT-based controllers, the proposed method produced more desirable response in terms of faster settling time, less percentage of overshoot with reduced ringing, smaller control effort required and wider leverage of uncertainty range.
format	Conference or Workshop Item
author	Mansor, Hasmah Khan, Sheroz Gunawan, Teddy Surya Mohd Noor, Samsul Bahari
author_facet	Mansor, Hasmah Khan, Sheroz Gunawan, Teddy Surya Mohd Noor, Samsul Bahari
author_sort	Mansor, Hasmah
title	A development of self-tuning quantitative feedback theory
title_short	A development of self-tuning quantitative feedback theory
title_full	A development of self-tuning quantitative feedback theory
title_fullStr	A development of self-tuning quantitative feedback theory
title_full_unstemmed	A development of self-tuning quantitative feedback theory
title_sort	development of self-tuning quantitative feedback theory
publisher	IEEExplore
publishDate	2012
url	http://irep.iium.edu.my/25642/ http://irep.iium.edu.my/25642/ http://irep.iium.edu.my/25642/ http://irep.iium.edu.my/25642/1/06271341on_IEEExplore.pdf
first_indexed	2023-09-18T20:38:12Z
last_indexed	2023-09-18T20:38:12Z
_version_	1777409188551458816

A development of self-tuning quantitative feedback theory

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