Neural Network Controller Implementation on a Supersonic Separator

Supersonic Separator was developed in the last decade to replace the conventional method of removing water content from raw natural gas by chemicals. Its first commercialization was in 2004 on Shell B-11 Platform and still in use up until today. The controller in use currently implemented a PID algo...

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Main Authors: Mohamad Hanif, Noor Hazrin Hany, Mokhtar, Khairil Anuar
Format: Conference or Workshop Item
Published: 2009
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Online Access:http://eprints.utp.edu.my/1837/1/E-12.pdf
http://eprints.utp.edu.my/1837/
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spelling my.utp.eprints.18372017-03-20T01:56:59Z Neural Network Controller Implementation on a Supersonic Separator Mohamad Hanif, Noor Hazrin Hany Mokhtar, Khairil Anuar TK Electrical engineering. Electronics Nuclear engineering Supersonic Separator was developed in the last decade to replace the conventional method of removing water content from raw natural gas by chemicals. Its first commercialization was in 2004 on Shell B-11 Platform and still in use up until today. The controller in use currently implemented a PID algorithm to control the position of the shockwave within the separator. This shockwave is essential for the separation process. However, a PID control paradigm is quite inefficient due to the non-linear properties of pressure distribution along the shockwave and the behavior of a shockwave that fluctuates generally around 500Hz. Implementation of a Neural Network based controller on the system may yield better results in terms of controllability and stability as shown by some research due to its predictive and adaptive characteristic. 2009 Conference or Workshop Item PeerReviewed application/pdf http://eprints.utp.edu.my/1837/1/E-12.pdf Mohamad Hanif, Noor Hazrin Hany and Mokhtar, Khairil Anuar (2009) Neural Network Controller Implementation on a Supersonic Separator. In: IEEE Student Conference in Research & Development, 16-18 November 2009, UPM, Malaysia. http://eprints.utp.edu.my/1837/
institution Universiti Teknologi Petronas
building UTP Resource Centre
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Petronas
content_source UTP Institutional Repository
url_provider http://eprints.utp.edu.my/
topic TK Electrical engineering. Electronics Nuclear engineering
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Mohamad Hanif, Noor Hazrin Hany
Mokhtar, Khairil Anuar
Neural Network Controller Implementation on a Supersonic Separator
description Supersonic Separator was developed in the last decade to replace the conventional method of removing water content from raw natural gas by chemicals. Its first commercialization was in 2004 on Shell B-11 Platform and still in use up until today. The controller in use currently implemented a PID algorithm to control the position of the shockwave within the separator. This shockwave is essential for the separation process. However, a PID control paradigm is quite inefficient due to the non-linear properties of pressure distribution along the shockwave and the behavior of a shockwave that fluctuates generally around 500Hz. Implementation of a Neural Network based controller on the system may yield better results in terms of controllability and stability as shown by some research due to its predictive and adaptive characteristic.
format Conference or Workshop Item
author Mohamad Hanif, Noor Hazrin Hany
Mokhtar, Khairil Anuar
author_facet Mohamad Hanif, Noor Hazrin Hany
Mokhtar, Khairil Anuar
author_sort Mohamad Hanif, Noor Hazrin Hany
title Neural Network Controller Implementation on a Supersonic Separator
title_short Neural Network Controller Implementation on a Supersonic Separator
title_full Neural Network Controller Implementation on a Supersonic Separator
title_fullStr Neural Network Controller Implementation on a Supersonic Separator
title_full_unstemmed Neural Network Controller Implementation on a Supersonic Separator
title_sort neural network controller implementation on a supersonic separator
publishDate 2009
url http://eprints.utp.edu.my/1837/1/E-12.pdf
http://eprints.utp.edu.my/1837/
_version_ 1738655156120059904
score 13.211869