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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. Meanwh...

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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: IEEE 2012
Online Access:http://psasir.upm.edu.my/id/eprint/41239/1/A%20development%20of%20self-tuning%20quantitative%20feedback%20theory.pdf
http://psasir.upm.edu.my/id/eprint/41239/
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spelling my.upm.eprints.412392018-03-30T07:42:22Z http://psasir.upm.edu.my/id/eprint/41239/ A development of self-tuning quantitative feedback theory Mansor, Hasmah Khan, Sheroz Gunawan, Teddy Surya Mohd Noor, Samsul Bahari 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. IEEE 2012 Conference or Workshop Item PeerReviewed text en http://psasir.upm.edu.my/id/eprint/41239/1/A%20development%20of%20self-tuning%20quantitative%20feedback%20theory.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, Kuala Lumpur, Malaysia. (pp. 873-876). 10.1109/ICCCE.2012.6271341
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
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
spellingShingle Mansor, Hasmah
Khan, Sheroz
Gunawan, Teddy Surya
Mohd Noor, Samsul Bahari
A development of self-tuning quantitative feedback theory
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 IEEE
publishDate 2012
url http://psasir.upm.edu.my/id/eprint/41239/1/A%20development%20of%20self-tuning%20quantitative%20feedback%20theory.pdf
http://psasir.upm.edu.my/id/eprint/41239/
_version_ 1643832940949405696
score 13.211869

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