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...
| Main Authors: | , , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
IEEExplore
2012
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| Subjects: | |
| 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 |
| Summary: | 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. |
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