For Libraries For Publication Open Access Downloads About Us Contact Us
Paper Titles
Swarm Intelligence Optimization Techniques in Mobile Path Planning - A Review
p.62
Performance Evaluation of Optical Networks Using Advanced Modulation Format
p.72
Event Based Formalization of Communication Properties for an E-Commerce Protocol: An Event-B Approach
p.78
Predicting Buildings Collapse due to Seismic Action in Lagos State
p.91
Determination of Physical and Mechanical Characteristics of Macro Sample of Water Saturated Peat
p.103
Kinetics and Isotherm Studies of Liquid Phase Adsorption of Cationic Dye onto Chitosan Synthesized from Crab Shells
p.112
Inferential Control of Fuel Additive Purity via Reactive Distillation Process
p.127
The Main Regularities of Ignition and Combustion of Coal-Water Fuels Produced from Brown, Flame and Gas Coals
p.141
Proposal and Analysis of a Model for Design and Development of Lean Supply Chain Strategy
p.158

Inferential Control of Fuel Additive Purity via Reactive Distillation Process

Article Preview

Abstract:

In this work, the control of the mole fraction of a fuel additive being produced in a reactive distillation column has been carried out using proportional-integral-derivative (PID) control. The fuel additive considered in this case was isopropyl alcohol, which was produced from the reaction between propylene and water. To accomplish the work, a ChemCAD model of the process was first developed and simulated to convergence before it was converted to dynamic type from which the dynamic responses of the system were generated and used, with the aid of MATLAB, to develop a transfer function model having the reboiler duty, the reflux ratio and the temperature of the bottom product as the input, the disturbance and the output variables of the process, respectively. The obtained transfer function model was used to develop the open-loop and the closed-loop Simulink models of the process that were also simulated. The closed-loop simulation was carried out with the objective of achieving a fuel additive product with a mole fraction of 0.97, and this was done using a PID controller that was applied inferentially via the product temperature. The results obtained showed that the control of the fuel additive mole fraction could be achieved inferentially, with PID controller tuned with Cohen-Coon and Simulink approaches, using product temperature.

You might also be interested in these eBooks
International Journal of Engineering Research in Africa Vol. 37 View Preview

Info:

Periodical:

International Journal of Engineering Research in Africa (Volume 37)

Pages:

127-140

DOI:

https://doi.org/10.4028/www.scientific.net/JERA.37.127

Citation:

Cite this paper

Online since:

August 2018

Authors:

Abdulwahab Giwa*, Edmund Iniyemi Yibo, Abel Adekanmi Adeyi

Keywords:

ChemCAD, Fuel Additive, Inferential Control, Isopropyl Alcohol, MATLAB/Simulink, Proportional-Integral-Derivative (PID), Reactive Distillation

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

© 2018 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

* - Corresponding Author

References

[1] Suthar, D.K.L., Rathod, P.P. and Patel, N.K. 2012. Performance and Emission by Effect of Fuel Additives For CI Engine Fuelled With Blend of Biodiesel And Diesel - A Review Study. Journal of Engineering Research and Studies, 3(4), 1-4.

Google Scholar

[2] Ali, O.M., Mamat, R. and Faizal, C.K.M. 2013. Improvement of Blended Biodiesel Fuel Properties with Ethanol Additive. International Journal of Advanced Science and Technology, 55, 21-32.

Google Scholar

[3] Shekhawat, V.S. and Padwa, R.S. 2015. Role of Additives and their Influence on Performance of Engine for Petroleum Diesel Fuel, Oxygenated-Diesel Blend: A Review. International Journal of Engineering Research & Technology, 4(7), 1-5.

DOI: 10.17577/ijertv4is070027

Google Scholar

[4] Maji, S., Ahmed, S., Siddiqui, W.A., Aggarwal, S. and Kumar, A. 2015. Impact of Di-methyl Ether (DME) as an Additive Fuel for Compression Ignition Engine in Reduction of Urban Air Pollution. American Journal of Environmental Protection, 3(2), 48-52.

DOI: 10.15680/ijirset.2014.0311020

Google Scholar

[5] Giwa, A., Giwa , S.O. and Hapoglu, H. 2013. Adaptive Neuro-Fuzzy Inference Systems (ANFIS) Modeling of Reactive Distillation Process. ARPN Journal of Engineering and Applied Sciences. 8(7), 473-479.

Google Scholar

[6] Giwa, A. and Giwa, S.O. 2016. Modelling and Simulation of a Reactive Distillation Process for Fuel Additive Production. Journal of Environmental Science, Computer Science and Engineering & Technology, Section C: Engineering & Technology. 5(1), 63-74.

Google Scholar

[7] Giwa A. 2016. PI and PID Control of a Fuel Additive Reactive Distillation Process. ARPN Journal of Engineering and Applied Sciences, 11(11), 6779-6793.

Google Scholar

[8] Giwa, A. 2012. Steady-State Modeling of n-Butyl Acetate Transesterification Process Using Aspen Plus: Conventional versus Integrated, ARPN Journal of Engineering and Applied Sciences, 7(12), 1555-1564.

Google Scholar

[9] Giwa, A. 2013. Methyl Acetate Reactive Distillation Process Modeling, Simulation and Optimization Using Aspen Plus, ARPN Journal of Engineering and Applied Sciences, 8(5), 386-392.

Google Scholar

[10] Giwa, S.O., Giwa, A. and Hapoglu, H. 2013. Investigating the Effects of Some Parameters on Hydrogen Sulphide Stripping Column Using Aspen HYSYS. ARPN Journal of Engineering and Applied Sciences, 8(5), 338-347.

Google Scholar

[11] Giwa, A. and Ogunware, M.A. 2018. Modelling, Simulation and Control of a Reactive Distillation Process for Biodiesel Production. ABUAD Journal of Engineering Research and Development, 1(1), 49-60.

Google Scholar

[12] Giwa, A., Bello, A., and Giwa, S.O. 2014. Performance Analyses of Fatty Acids in Reactive Distillation Process for Biodiesel Production. International Journal of Scientific & Engineering Research, 5(12), 529-540.

Google Scholar

[13] Giwa, A., Bello, A. and Giwa, S.O. 2015. Artificial Neural Network Modeling of a Reactive Distillation Process for Biodiesel Production. International Journal of Scientific & Engineering Research, 6(1), 1175- 1191.

Google Scholar

[14] Giwa, A., Giwa, S.O. and Olugbade, E.A. 2018. Application of Aspen HYSYS Process Simulator in Green Energy Revolution: A Case Study of Biodiesel Production. ARPN Journal of Engineering and Applied Sciences, 13(2), 569-581.

Google Scholar

[15] Giwa, A. and Karacan, S. 2012. Simulation and Optimization of Ethyl Acetate Reactive Packed Distillation Process Using Aspen Hysys, The Online Journal of Science and Technology, 2(2), 57-63.

Google Scholar

[16] Giwa, A. and Karacan, S. 2012. Nonlinear Black-Box Modeling of a Reactive Distillation Process. International Journal of Engineering Research & Technology, 1(7), 548-557.

Google Scholar

[17] Giwa, A. and Karacan, S. 2012. Decoupling Control of a Reactive Distillation Process Using Tyreus-Luyben Technique. ARPN Journal of Engineering and Applied Sciences, 7(10), 1263-1272.

Google Scholar

[18] Giwa, A. and Giwa, S.O. 2013. Isopropyl Myristate Production Process Optimization Using Response Surface Methodology and MATLAB. International Journal of Engineering Research & Technology, 2(1), 853-862.

Google Scholar

[19] Giwa, A. and Giwa, S.O. 2013. Estimating the Optimum Operating Parameters of Olefin Metathesis Reactive Distillation Process. ARPN Journal of Engineering and Applied Sciences, 8(8), 614-624.

Google Scholar

[20] Giwa, A., Giwa, S.O., Bayram, I. and Karacan, S. 2013. Simulations and Economic Analyses of Ethyl Acetate Productions by Conventional and Reactive Distillation Processes Using Aspen Plus. International Journal of Engineering Research & Technology, 2(8), 594-605.

Google Scholar

[21] Giwa, A. 2014. Solving the Dynamic Models of Reactive Packed Distillation Process Using Difference Formula Approaches. ARPN Journal of Engineering and Applied Sciences, 9(2), 98-108.

Google Scholar

[22] Giwa, A. 2018. Monothetic Analysis of Octene Metathesis Reactive Distillation Process. ARPN Journal of Engineering and Applied Sciences, 13(4), 1251-1264.

Google Scholar

[23] Giwa, A. and Karacan, S. 2012. Modeling and Simulation of a Reactive Packed Distillation Column Using Delayed Neural Networks. Chaotic Modeling and Simulation, 2(1), 101-108.

Google Scholar

[24] Giwa, A. and Giwa, S.O. 2013. Layer-Recurrent Neural Network Modelling of Reactive Distillation Process. Chaotic Modeling and Simulation, 2(4), 647-656.

Google Scholar

[25] Giwa, S.O., Adeyi, A.A. and Giwa, A. 2016. Application of Model Predictive Control to Renewable Energy Development via Reactive Distillation Process. International Journal of Engineering Research in Africa, 27, 95-110.

DOI: 10.4028/www.scientific.net/jera.27.95

Google Scholar

[26] Sneesby, M. G., Tade, M.O., Datta, R. and Smith, T. N. 1997. ETBE Synthesis via Reactive Distillation. 2. Dynamic Simulation and Control Aspects. Industrial and Engineering Chemistry Research. 36, 1870-1881.

DOI: 10.1021/ie970053y

Google Scholar

[27] Sneesby, M.G., Tade, M.O. and Smith, T.N. 1999. Two-Point Control of a Reactive Distillation Column for Composition and Conversion. Journal of Process Control. 9, 19-31.

DOI: 10.1016/s0959-1524(98)00007-9

Google Scholar

[28] Monroy-Loperena, R., Perez-Cisneros, E. and Alvarez-Ramirez, J. 2000. A Robust PI Control Configuration for a High-Purity Ethylene Glycol Reactive Distillation Column. Chemical Engineering Science. 55(21), 4925-4937.

DOI: 10.1016/s0009-2509(00)00124-x

Google Scholar

[29] Al-Arfaj, M. and Luyben, W.L. 2002. Control Study of Ethyl Tert-Butyl Ether Reactive Distillation. Industrial and Engineering Chemistry Research. 41, 3784-3796.

DOI: 10.1021/ie010432y

Google Scholar

[30] Al-Arfaj, M. and Luyben, W.L. 2002. Control of Ethylene Glycol Reactive Distillation Column. AIChE Journal. 48, 905-908.

DOI: 10.1002/aic.690480424

Google Scholar

[31] Bisowarno, B.H., Tian, Y. and Tadé, M.O. 2003. Model Gain Scheduling Control of an Ethyl Tert-Butyl Ether Reactive Distillation Column. Industrial and Engineering Chemistry Research. 42, 3584-3591.

DOI: 10.1021/ie020763q

Google Scholar

[32] Tian, Y., Zhao, F., Bisowarno, B.H. and Tadé, M.O. 2003. Pattern-Based Predictive Control for ETBE Reactive Distillation. Journal of Process Control. 13, 57-67.

DOI: 10.1016/s0959-1524(02)00011-2

Google Scholar

[33] Khaledi, R. and Young, B.R. 2005. Modeling and Model Predictive Control of Composition and Conversion in an ETBE Reactive Distillation Column. Industrial and Engineering Chemistry Research, 44, 3134-3145.

DOI: 10.1021/ie049274b

Google Scholar

[34] Wang, S.J. and Wong, D.S.H. 2006. Control of Reactive Distillation Production of High-Purity Isopropanol. Journal of Process Control. 16, 385-394.

DOI: 10.1016/j.jprocont.2005.06.015

Google Scholar

[35] Chemstations. 2017. ChemCAD 7.1.2.9917. Chemstations Inc., Texas.

Google Scholar

[36] MathWorks. 2017. MATLAB, the Language of Technical Computing. The MathWorks, Inc., Natick.

Google Scholar

© 2025 Trans Tech Publications Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies. For open access content, terms of the Creative Commons licensing CC-BY are applied.
Scientific.Net is a registered trademark of Trans Tech Publications Ltd.