Genetic Model Reference Adaptive Control of Shell Heavy Oil Fractionator
(Sprache: Englisch)
Stable and efficient control scheme is essential for the operation of an oil fractionating distillation unit. However, due to high complex non-linear dynamic behaviour, many of the conventional control schemes deteriorate in performance over a wide range of...
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Stable and efficient control scheme is essential for the operation of an oil fractionating distillation unit. However, due to high complex non-linear dynamic behaviour, many of the conventional control schemes deteriorate in performance over a wide range of operating regions. Therefore, a Genetic Model Reference Adaptive Control (GMRAC) scheme was developed to control a crude oil distillation unit in this study.Shell Heavy Oil Fractionator (SHOF) model was used in the design and analyses of the GMRAC control system. It was subjected to interaction analysis using Relative Gain Array (RGA). Static and dynamicdecouplers were designed using inverse of process gain matrix which is 3x3 array and feedforward control design respectively. The decoupled model was used to design a GMRAC using a second order reference model. This was optimized using genetic algorithm technique. This study showed that closed loop response for GMRAC gave a faster settling time with more stability compared to PI controllers. Therefore, GMRAC is recommended for use in crude oil distillation unit.
Autoren-Porträt von Aminah Abolore Sulayman, Dr. Dauda Olurotimi Araromi, Olajide Olukayode Ajala
Abolore Sulayman, AminahAminah Abolore Sulayman research interest are process modelling and control. She is a Registered Engineer under COREN. Dr. Dauda Olurotimi Araromi is an Associate Professor in Chemical Engineering, Ladoke Akintola Univ. of Technology.Olajide Olukayode Ajala research interest are process modelling and control and renewable energy.
Bibliographische Angaben
- Autoren: Aminah Abolore Sulayman , Dr. Dauda Olurotimi Araromi , Olajide Olukayode Ajala
- 88 Seiten, Maße: 22 cm, Kartoniert (TB), Englisch
- Verlag: LAP Lambert Academic Publishing
- ISBN-10: 620268271X
- ISBN-13: 9786202682718
Sprache:
Englisch
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