Advanced control of a fluidized bed using a model-predictive controller

The control of fluidized-bed processes remains an area of intensive research due to their complexity and the inherent nonlinearity and varying operational dynamics involved. There are a variety of problems in chemical engineering that can be formulated as Nonlinear Programming (NLP) problems. The qu...

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Main Authors: Ibrehem, Ahmmed S., Hussain, Mohd Azlan, Ghasem, Nayef M.
Format: Article
Language:English
Published: American-Eurasian Network for Scientific Information, Jordan 2009
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Online Access:http://eprints.um.edu.my/7036/1/Advanced_control_of_a_fluidized_bed_using_a_model-predictive_controller.pdf
http://eprints.um.edu.my/7036/
http://www.ajbasweb.com/old/ajbas/2009/3954-3974.pdf
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spelling my.um.eprints.70362019-11-14T01:43:24Z http://eprints.um.edu.my/7036/ Advanced control of a fluidized bed using a model-predictive controller Ibrehem, Ahmmed S. Hussain, Mohd Azlan Ghasem, Nayef M. TA Engineering (General). Civil engineering (General) TP Chemical technology The control of fluidized-bed processes remains an area of intensive research due to their complexity and the inherent nonlinearity and varying operational dynamics involved. There are a variety of problems in chemical engineering that can be formulated as Nonlinear Programming (NLP) problems. The quality of the solution developed significantly affects the performance of such a system. Controller design involves tuning of the process controllers and their implementation to achieve a specified performance of the controlled variables. Here we used a Sequential Quadratic Programming (SQP) method to tackle the constrained high-NLP problem, in this case a modified mathematical model of gas-phase olefin polymerisation in a fluidized-bed catalytic reactor. The objective of this work was to present a comparative study; PID control was compared to an advanced neural network-based MPC decentralised controller, and the effect of SQP on the performance of the controlled variables was studied. The two control approaches were evaluated for set-point tracking and load rejection properties, both giving acceptable results. American-Eurasian Network for Scientific Information, Jordan 2009 Article PeerReviewed application/pdf en http://eprints.um.edu.my/7036/1/Advanced_control_of_a_fluidized_bed_using_a_model-predictive_controller.pdf Ibrehem, Ahmmed S. and Hussain, Mohd Azlan and Ghasem, Nayef M. (2009) Advanced control of a fluidized bed using a model-predictive controller. Australian Journal of Basic and Applied Sciences, 3 (4). pp. 3954-3974. ISSN 1991-8178 http://www.ajbasweb.com/old/ajbas/2009/3954-3974.pdf
institution Universiti Malaya
building UM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaya
content_source UM Research Repository
url_provider http://eprints.um.edu.my/
language English
topic TA Engineering (General). Civil engineering (General)
TP Chemical technology
spellingShingle TA Engineering (General). Civil engineering (General)
TP Chemical technology
Ibrehem, Ahmmed S.
Hussain, Mohd Azlan
Ghasem, Nayef M.
Advanced control of a fluidized bed using a model-predictive controller
description The control of fluidized-bed processes remains an area of intensive research due to their complexity and the inherent nonlinearity and varying operational dynamics involved. There are a variety of problems in chemical engineering that can be formulated as Nonlinear Programming (NLP) problems. The quality of the solution developed significantly affects the performance of such a system. Controller design involves tuning of the process controllers and their implementation to achieve a specified performance of the controlled variables. Here we used a Sequential Quadratic Programming (SQP) method to tackle the constrained high-NLP problem, in this case a modified mathematical model of gas-phase olefin polymerisation in a fluidized-bed catalytic reactor. The objective of this work was to present a comparative study; PID control was compared to an advanced neural network-based MPC decentralised controller, and the effect of SQP on the performance of the controlled variables was studied. The two control approaches were evaluated for set-point tracking and load rejection properties, both giving acceptable results.
format Article
author Ibrehem, Ahmmed S.
Hussain, Mohd Azlan
Ghasem, Nayef M.
author_facet Ibrehem, Ahmmed S.
Hussain, Mohd Azlan
Ghasem, Nayef M.
author_sort Ibrehem, Ahmmed S.
title Advanced control of a fluidized bed using a model-predictive controller
title_short Advanced control of a fluidized bed using a model-predictive controller
title_full Advanced control of a fluidized bed using a model-predictive controller
title_fullStr Advanced control of a fluidized bed using a model-predictive controller
title_full_unstemmed Advanced control of a fluidized bed using a model-predictive controller
title_sort advanced control of a fluidized bed using a model-predictive controller
publisher American-Eurasian Network for Scientific Information, Jordan
publishDate 2009
url http://eprints.um.edu.my/7036/1/Advanced_control_of_a_fluidized_bed_using_a_model-predictive_controller.pdf
http://eprints.um.edu.my/7036/
http://www.ajbasweb.com/old/ajbas/2009/3954-3974.pdf
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score 13.211869