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Design of QFT-based self-tuning deadbeat controller

This paper presents a design method of self-tuning Quantitative Feedback Theory (QFT) by using improved deadbeat control algorithm. QFT is a technique to achieve robust control with pre-defined specifications whereas deadbeat is an algorithm that could bring the output to steady state with minimum...

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Main Authors:	Mansor, Hasmah, Mohd Noor, Samsul Bahari
Format:	Article
Language:	English
Published:	World Academy of Science, Engineering and Technology (W A S E T) 2013
Subjects:	S Agriculture (General) T Technology (General)
Online Access:	http://irep.iium.edu.my/31072/1/WASETpublished.pdf http://irep.iium.edu.my/31072/ http://www.waset.org
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spelling	my.iium.irep.310722013-07-31T01:14:47Z http://irep.iium.edu.my/31072/ Design of QFT-based self-tuning deadbeat controller Mansor, Hasmah Mohd Noor, Samsul Bahari S Agriculture (General) T Technology (General) This paper presents a design method of self-tuning Quantitative Feedback Theory (QFT) by using improved deadbeat control algorithm. QFT is a technique to achieve robust control with pre-defined specifications whereas deadbeat is an algorithm that could bring the output to steady state with minimum step size. Nevertheless, usually there are large peaks in the deadbeat response.By integrating QFT specifications into deadbeat algorithm, the large peaks could be tolerated. On the other hand, emerging QFT with adaptive element will produce a robust controller with wider coverage of uncertainty. By combining QFT-based deadbeat algorithm and adaptive element, superior controller that is called self tuning QFT-based deadbeat controller could be achieved. The output response that is fast, robust and adaptive is expected. Using a grain dryer plant model as a pilot case-study, the performance of the proposed method has been evaluated and analyzed. Grain drying process is very complex with highly nonlinear behaviour, long delay, affected by environmental changes and affected by disturbances. Performance comparisons have been performed between the proposed self-tuning QFT-based deadbeat, standard QFT and standard dead-beat controllers. The efficiency of the self-tuning QFT based dead-beat controller has been proven from the tests results in terms of controller’s parameters are updated online, less percentage of overshoot and settling time especially when there are variations in the plant. World Academy of Science, Engineering and Technology (W A S E T) 2013-07 Article REM application/pdf en http://irep.iium.edu.my/31072/1/WASETpublished.pdf Mansor, Hasmah and Mohd Noor, Samsul Bahari (2013) Design of QFT-based self-tuning deadbeat controller. World Academy of Science, Engineering and Technology, 79. pp. 1291-1293. ISSN 1307-6884 http://www.waset.org
institution	Universiti Islam Antarabangsa Malaysia
building	IIUM Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	International Islamic University Malaysia
content_source	IIUM Repository (IREP)
url_provider	http://irep.iium.edu.my/
language	English
topic	S Agriculture (General) T Technology (General)
spellingShingle	S Agriculture (General) T Technology (General) Mansor, Hasmah Mohd Noor, Samsul Bahari Design of QFT-based self-tuning deadbeat controller
description	This paper presents a design method of self-tuning Quantitative Feedback Theory (QFT) by using improved deadbeat control algorithm. QFT is a technique to achieve robust control with pre-defined specifications whereas deadbeat is an algorithm that could bring the output to steady state with minimum step size. Nevertheless, usually there are large peaks in the deadbeat response.By integrating QFT specifications into deadbeat algorithm, the large peaks could be tolerated. On the other hand, emerging QFT with adaptive element will produce a robust controller with wider coverage of uncertainty. By combining QFT-based deadbeat algorithm and adaptive element, superior controller that is called self tuning QFT-based deadbeat controller could be achieved. The output response that is fast, robust and adaptive is expected. Using a grain dryer plant model as a pilot case-study, the performance of the proposed method has been evaluated and analyzed. Grain drying process is very complex with highly nonlinear behaviour, long delay, affected by environmental changes and affected by disturbances. Performance comparisons have been performed between the proposed self-tuning QFT-based deadbeat, standard QFT and standard dead-beat controllers. The efficiency of the self-tuning QFT based dead-beat controller has been proven from the tests results in terms of controller’s parameters are updated online, less percentage of overshoot and settling time especially when there are variations in the plant.
format	Article
author	Mansor, Hasmah Mohd Noor, Samsul Bahari
author_facet	Mansor, Hasmah Mohd Noor, Samsul Bahari
author_sort	Mansor, Hasmah
title	Design of QFT-based self-tuning deadbeat controller
title_short	Design of QFT-based self-tuning deadbeat controller
title_full	Design of QFT-based self-tuning deadbeat controller
title_fullStr	Design of QFT-based self-tuning deadbeat controller
title_full_unstemmed	Design of QFT-based self-tuning deadbeat controller
title_sort	design of qft-based self-tuning deadbeat controller
publisher	World Academy of Science, Engineering and Technology (W A S E T)
publishDate	2013
url	http://irep.iium.edu.my/31072/1/WASETpublished.pdf http://irep.iium.edu.my/31072/ http://www.waset.org
_version_	1643609979799732224
score	13.211869

Design of QFT-based self-tuning deadbeat controller

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