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...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Academic Journals
2011
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| Online Access: | http://psasir.upm.edu.my/id/eprint/22783/ http://psasir.upm.edu.my/id/eprint/22783/1/22783.pdf |
| _version_ | 1848844579678191616 |
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| author | Mansor, Hasmah Mohd Noor, Samsul Bahari Raja Ahmad, Raja Mohd Kamil Taip, Farah Saleena |
| author_facet | Mansor, Hasmah Mohd Noor, Samsul Bahari Raja Ahmad, Raja Mohd Kamil Taip, Farah Saleena |
| author_sort | Mansor, Hasmah |
| building | UPM Institutional Repository |
| collection | Online Access |
| 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. |
| first_indexed | 2025-11-15T08:33:10Z |
| format | Article |
| id | upm-22783 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T08:33:10Z |
| publishDate | 2011 |
| publisher | Academic Journals |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-227832020-04-15T16:22:24Z http://psasir.upm.edu.my/id/eprint/22783/ Online quantitative feedback theory (QFT) -based self-tuning controller for grain drying process Mansor, Hasmah Mohd Noor, Samsul Bahari Raja Ahmad, Raja Mohd Kamil Taip, Farah Saleena 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 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/22783/1/22783.pdf Mansor, Hasmah and Mohd Noor, Samsul Bahari and Raja Ahmad, Raja Mohd 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). art. no. 4DB49DF32223. pp. 6520-6534. ISSN 1992-2248 https://academicjournals.org/journal/SRE/article-abstract/4DB49DF32223 10.5897/SRE11.1337 |
| spellingShingle | Mansor, Hasmah Mohd Noor, Samsul Bahari Raja Ahmad, Raja Mohd Kamil Taip, Farah Saleena Online quantitative feedback theory (QFT) -based self-tuning controller for grain drying process |
| title | 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_short | 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 |
| url | http://psasir.upm.edu.my/id/eprint/22783/ http://psasir.upm.edu.my/id/eprint/22783/ http://psasir.upm.edu.my/id/eprint/22783/ http://psasir.upm.edu.my/id/eprint/22783/1/22783.pdf |