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Metamodeling approach for PID controller optimization in an evaporator process

This paper aims to describe Metamodeling approach, a technique that can be utilized to tune controller parameters for a non-linear process quickly, and how it is used to solve real world engineering problems by applying it to the problem of designing a proportional-integral-derivative (PID) controll...

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التفاصيل البيبلوغرافية
المؤلفون الرئيسيون: Shah, M. F. N., Zainal, M. A., Faruq, A., Abdullah, Shahrum Shah
التنسيق: Book Section
منشور في: IEEE 2011
الموضوعات:
T Technology
الوصول للمادة أونلاين:http://eprints.utm.my/id/eprint/29356/
http://dx.doi.org/ 10.1109/ICMSAO.2011.5775616
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id my.utm.29356
record_format eprints
spelling my.utm.293562017-02-05T00:00:07Z http://eprints.utm.my/id/eprint/29356/ Metamodeling approach for PID controller optimization in an evaporator process Shah, M. F. N. Zainal, M. A. Faruq, A. Abdullah, Shahrum Shah T Technology This paper aims to describe Metamodeling approach, a technique that can be utilized to tune controller parameters for a non-linear process quickly, and how it is used to solve real world engineering problems by applying it to the problem of designing a proportional-integral-derivative (PID) controller. The process used in this study is a single input single output (SISO) evaporator system which is intrinsically non-linear plant. The Radial Basis Function Neural Network Metamodel used was able to give a good approximation to the optimum controller parameters in this case. Also Genetic Algorithm (GA) and Ant Colony Optimization (ACO) are used to design the controller parameters and are compared with Metamodeling. IEEE 2011 Book Section PeerReviewed Shah, M. F. N. and Zainal, M. A. and Faruq, A. and Abdullah, Shahrum Shah (2011) Metamodeling approach for PID controller optimization in an evaporator process. In: 2011 Fourth International Conference on Modeling, Simulation and Applied Optimization. IEEE, New Jersey, 001-004. ISBN 978-145770005-7 http://dx.doi.org/ 10.1109/ICMSAO.2011.5775616 10.1109/ICMSAO.2011.5775616
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
topic T Technology
spellingShingle T Technology
Shah, M. F. N.
Zainal, M. A.
Faruq, A.
Abdullah, Shahrum Shah
Metamodeling approach for PID controller optimization in an evaporator process
description This paper aims to describe Metamodeling approach, a technique that can be utilized to tune controller parameters for a non-linear process quickly, and how it is used to solve real world engineering problems by applying it to the problem of designing a proportional-integral-derivative (PID) controller. The process used in this study is a single input single output (SISO) evaporator system which is intrinsically non-linear plant. The Radial Basis Function Neural Network Metamodel used was able to give a good approximation to the optimum controller parameters in this case. Also Genetic Algorithm (GA) and Ant Colony Optimization (ACO) are used to design the controller parameters and are compared with Metamodeling.
format Book Section
author Shah, M. F. N.
Zainal, M. A.
Faruq, A.
Abdullah, Shahrum Shah
author_facet Shah, M. F. N.
Zainal, M. A.
Faruq, A.
Abdullah, Shahrum Shah
author_sort Shah, M. F. N.
title Metamodeling approach for PID controller optimization in an evaporator process
title_short Metamodeling approach for PID controller optimization in an evaporator process
title_full Metamodeling approach for PID controller optimization in an evaporator process
title_fullStr Metamodeling approach for PID controller optimization in an evaporator process
title_full_unstemmed Metamodeling approach for PID controller optimization in an evaporator process
title_sort metamodeling approach for pid controller optimization in an evaporator process
publisher IEEE
publishDate 2011
url http://eprints.utm.my/id/eprint/29356/
http://dx.doi.org/ 10.1109/ICMSAO.2011.5775616
_version_ 1643648282144014336
score 13.250246

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