Online Quantitative feedback theory (QFT)-based self-tuning controller for grain drying process

This paper presents a development of QFT-based self-tuning controller for a conveyor belt type grain dryer plant. Grain drying process is complex due to long time delay, presence of disturbances and plant uncertainty. QFT technique potentially has excellent solution towards this problem due to its w...

Full description

Bibliographic Details
Main Authors: Mansor, Hasmah, Mohd Noor, Samsul Bahari, Raja Ahmad, Raja Kamil, Taip, Farah Saleena
Format: Article
Language:English
Published: Academic Journals 2011
Subjects:
Online Access:http://irep.iium.edu.my/12334/
http://irep.iium.edu.my/12334/
http://irep.iium.edu.my/12334/
http://irep.iium.edu.my/12334/1/Mansor%2520et%2520al.pdf
id iium-12334
recordtype eprints
spelling iium-123342011-12-23T02:04:24Z http://irep.iium.edu.my/12334/ Online Quantitative feedback theory (QFT)-based self-tuning controller for grain drying process Mansor, Hasmah Mohd Noor, Samsul Bahari Raja Ahmad, Raja Kamil Taip, Farah Saleena TA Engineering (General). Civil engineering (General) TK Electrical engineering. Electronics Nuclear engineering This paper presents a development of QFT-based self-tuning controller for a conveyor belt type grain dryer plant. Grain drying process is complex due to long time delay, presence of disturbances and plant uncertainty. QFT technique potentially has excellent solution towards this problem due to its well known capability to achieve robust performance regardless parameters variation and disturbances. The mathematical model of the grain dryer plant is obtained using system identification based on real-time input/output data. A fixed robust controller could be designed using QFT technique; nevertheless the uncertainty range must be defined. However, in grain drying process, the parameters’ variations are unpredictable and may exceed the defined uncertainty ranges. Therefore, adaptive control with integrated Quantitative Feedback Theory (QFT) constraints is proposed to adapt larger parameters variation. Improved results are obtained by using the proposed method as compared to standard QFT procedure in terms of smaller percentage overshoot and shorter settling time when dealing with larger uncertainty range. In addition, the design methodology of the proposed controller design (loop shaping) was improved such that the dependency on human skills was removed and the controller design was done online. Academic Journals 2011-12-16 Article PeerReviewed application/pdf en http://irep.iium.edu.my/12334/1/Mansor%2520et%2520al.pdf Mansor, Hasmah and Mohd Noor, Samsul Bahari and Raja Ahmad, Raja Kamil and Taip, Farah Saleena (2011) Online Quantitative feedback theory (QFT)-based self-tuning controller for grain drying process. Scientific Research and Essays, 6 (31). pp. 6520-6534. ISSN 1992-2248 http://www.academicjournals.org/SRE/ DOI:10.5897/SRE11.1337
repository_type Digital Repository
institution_category Local University
institution International Islamic University Malaysia
building IIUM Repository
collection Online Access
language English
topic TA Engineering (General). Civil engineering (General)
TK Electrical engineering. Electronics Nuclear engineering
spellingShingle TA Engineering (General). Civil engineering (General)
TK Electrical engineering. Electronics Nuclear engineering
Mansor, Hasmah
Mohd Noor, Samsul Bahari
Raja Ahmad, Raja Kamil
Taip, Farah Saleena
Online Quantitative feedback theory (QFT)-based self-tuning controller for grain drying process
description This paper presents a development of QFT-based self-tuning controller for a conveyor belt type grain dryer plant. Grain drying process is complex due to long time delay, presence of disturbances and plant uncertainty. QFT technique potentially has excellent solution towards this problem due to its well known capability to achieve robust performance regardless parameters variation and disturbances. The mathematical model of the grain dryer plant is obtained using system identification based on real-time input/output data. A fixed robust controller could be designed using QFT technique; nevertheless the uncertainty range must be defined. However, in grain drying process, the parameters’ variations are unpredictable and may exceed the defined uncertainty ranges. Therefore, adaptive control with integrated Quantitative Feedback Theory (QFT) constraints is proposed to adapt larger parameters variation. Improved results are obtained by using the proposed method as compared to standard QFT procedure in terms of smaller percentage overshoot and shorter settling time when dealing with larger uncertainty range. In addition, the design methodology of the proposed controller design (loop shaping) was improved such that the dependency on human skills was removed and the controller design was done online.
format Article
author Mansor, Hasmah
Mohd Noor, Samsul Bahari
Raja Ahmad, Raja Kamil
Taip, Farah Saleena
author_facet Mansor, Hasmah
Mohd Noor, Samsul Bahari
Raja Ahmad, Raja Kamil
Taip, Farah Saleena
author_sort Mansor, Hasmah
title Online Quantitative feedback theory (QFT)-based self-tuning controller for grain drying process
title_short Online Quantitative feedback theory (QFT)-based self-tuning controller for grain drying process
title_full Online Quantitative feedback theory (QFT)-based self-tuning controller for grain drying process
title_fullStr Online Quantitative feedback theory (QFT)-based self-tuning controller for grain drying process
title_full_unstemmed Online Quantitative feedback theory (QFT)-based self-tuning controller for grain drying process
title_sort online quantitative feedback theory (qft)-based self-tuning controller for grain drying process
publisher Academic Journals
publishDate 2011
url http://irep.iium.edu.my/12334/
http://irep.iium.edu.my/12334/
http://irep.iium.edu.my/12334/
http://irep.iium.edu.my/12334/1/Mansor%2520et%2520al.pdf
first_indexed 2023-09-18T20:21:33Z
last_indexed 2023-09-18T20:21:33Z
_version_ 1777408140314148864