A Review of an Expert System Design for Crude Oil Distillation Column Using the Neural Networks Model and Process Optimization and Control Using Genetic Algorithm Framework

ABSTRACT

This paper presents a comprehensive review of various traditional systems of crude oil distillation column design, modeling, simulation, optimization and control methods. Artificial neural network (ANN), fuzzy logic (FL) and genetic algorithm (GA) framework were chosen as the best methodologies for design, optimization and control of crude oil distillation column. It was discovered that many past researchers used rigorous simulations which led to convergence problems that were time consuming. The use of dynamic mathematical models was also challenging as these models were also time dependent. The proposed methodologies use back-propagation algorithm to replace the convergence problem using error minimal method.

Cite this paper

L. Popoola, G. Babagana and A. Susu, "A Review of an Expert System Design for Crude Oil Distillation Column Using the Neural Networks Model and Process Optimization and Control Using Genetic Algorithm Framework,"*Advances in Chemical Engineering and Science*, Vol. 3 No. 2, 2013, pp. 164-170. doi: 10.4236/aces.2013.32020.

L. Popoola, G. Babagana and A. Susu, "A Review of an Expert System Design for Crude Oil Distillation Column Using the Neural Networks Model and Process Optimization and Control Using Genetic Algorithm Framework,"

References

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[2] W. Heather, “Refining Crude Oil,” The New Zealand Refining Company Ltd., Ruakaka, 2003.

[3] Z. E. H. Tonnang, “Distillation Column Control Using Artificial Neural Networks,” M.Sc Thesis, Microprocessors and Control Engineering, Department of Electrical and Electronics Engineering, Faculty of Technology, University of Ibadan, Ibadan, 2010.

[4] S. Christos and S. Dimitrios, “Introduction to Artificial Neural Network,” Research Report, 2001.

[5] H. L. Hoffman, D. E. Lupfer, L. A. Kane and B. A. Jensen, “Distillation Column, Basic and Advance Controls Process Control, Instrument Engineer Handbook,” 3rd Edition, Butherworth Heinemann, Oxford, 1995.

[6] T. M. Gowrie and V. V. C. Reddy, “Load Forecasting by a Novel Technique Using ANN,” ARPN Journal of Engineering and Applied Sciences, Vol. 3, No. 1, 2008, pp. 19-25.

[7] J. W. Sea, M. Oh and T. H. Lee, “Design Optimization of Crude Oil Distillation,” Chemical Engineering Technology, Vol. 23, No. 2, 2000, pp. 157-164. doi:10.1002/(SICI)1521-4125(200002)23:2<157::AID-CEAT157>3.0.CO;2-C

[8] J. McCarthy, “Some Expert System Need Common Sense,” Stanford University, Stanford, 1984.

[9] D. B. Manley, “Waste Minimization through Improved Process Thermodynamics: Crude Oil Fractionation,” The University of Missouri, Rolla, 1993.

[10] E. I. Santana and R. J. Zemp, “Thermodynamic Analysis of a Crude-Oil Fractionating Process,” 4th Mercosur Congress on Process Systems Engineering, Vol. 21S, 2001, pp. 523-528.

[11] J. J. Yu, C. H. Zhou, S. Tan and C. C. Hang, “An On-line Soft-Sensor for Control and Optimization of Crude Distillation Column,” Research Institute of Industrial Process Control, Zhejiang University, Hangzhou, 1997.

[12] K. H. Bawazir and A. Zilouchian, “Application of Neural Networks in Oil Refineries,” Proceedings of 1996 IEEE International Conference on Neural Networks, New Orleans, 1999.

[13] L. C.-K. Liau, T. C.-K. Yangb and M. T. Tsaib, “Expert System of a Crude Oil Distillation Unit for Process Optimization Using Neural Networks,” Expert Systems with Applications, Vol. 26, No. 2, 2004, pp. 247-255. doi:10.1016/S0957-4174(03)00139-8

[14] A. Torgashov, “Nonlinear Process Model-Based Self-Optimizing Control of Complex Crude Distillation Column,” European Symposium on Computer Aided Process Engineering-11, Vol. 9, 2001, pp. 793-798.

[15] M. F. Khairiyah, K. Fakhri and L. D. Peter, “Connectionist Models of a Crude Oil Distillation Column for Real Time Optimisation,” Regional Symposium on Chemical Engineering 2002, Songkla, 2002.

[16] M. Gadalla, M. Jobson and M. Smith, “Optimisation of Existing Heat—Integrated Refinery Distillation Systems,” Ph.D. Thesis, UMIST, Manchester, 2002.

[17] E. O. Okeke and A. A. Osakwe-Akofe, “Optimization of a Refinery Crude Distillation Unit in the Context of Total Energy Requirement,” APACT03, 28-30 April 2003, NNPC R&D Division, Port Harcourt, 2003.

[18] P. Domijan and D. Kalpic, “Off-Line Energy Optimization Model for Crude Distillation Unit,” Ph.D. Thesis, Department of Applied Mathematics, Faculty of Electrical Engineering and Computing, University of Zagreb, Zagreb, 2004.

[19] J. J. Macías-Hernández, P. Angelov and X. Zhou, “Soft Sensor for Predicting Crude Oil Distillation Side Streams Using Evolving Takagi-Sugeno Fuzzy Models. Results Outlined,” Proceedings of 2nd International Symposium on Evolving Fuzzy Systems, 7-9 September 2008, Lake District, IEEE Press, 2008, pp. 214-220.

[20] B. A. Zalizawati, “Development of Multiple-Input Multiple-Output and Multiple-Input Single-Output Neural Network Models for Continuous Distillation Column,” M.Sc Thesis, School of Chemical, 2008.

[21] R. Kanthasamy, “Nonlinear Model Predictive Control of a Distillation Column Using Hammerstein Model and Nonlinear Autoregressive Model with Exogenous Input,” Ph.D. Thesis, Universiti Sains Malaysia, 2009.

[22] J. Haydary and T. Pavlik, “Steady-State and Dynamic Simulation of Crude Oil Distillation Using ASPEN Plus and ASPEN Dynamics,” Petroleum and Coal, Vol. 51, No. 2, 2009, p. 100.

[23] R. Smith, M. Jobson, L. Chen and S. Farrokhpanah, “Heat Integrated Distillation System Design,” Centre for Process Integration, School of Chemical Engineering and Analytical Science, The University of Manchester, 2010.

[24] Y. Kansha, A. Kishimoto and A. Tsutsumi, “Application of the Self-Heat Recuperation Technology to Crude Oil Distillation,” Collaborative Research Centre for Energy Engineering, Institute of Industrial Science, The University of Tokyo, Tokyo, 2011.

[25] K. Hornik, M. Stinchcombe and H. White, “Multilayer Feedforward Neural Networks Are Universal Approximators,” Neural Networks, Vol. 2, No. 5, 1989, pp. 359-366. doi:10.1016/0893-6080(89)90020-8

[26] D. Rumelhart and J. McClelland, “Parallel Distributed Processing,” MIT Press, Cambridge, 1986.

[27] G. Daniel, “Principles of Artificial Neural Networks,” Advanced Series in Circuits and Systems, Vol. 51, No. 2, 2007, pp. 100-109.

[1] K. H. Bawazeer, “Prediction of Crude Oil Product Quality Parameters Using Neural Networks,” MS Thesis, Florida Atlantic University, Boca Raton, 1996.

[2] W. Heather, “Refining Crude Oil,” The New Zealand Refining Company Ltd., Ruakaka, 2003.

[3] Z. E. H. Tonnang, “Distillation Column Control Using Artificial Neural Networks,” M.Sc Thesis, Microprocessors and Control Engineering, Department of Electrical and Electronics Engineering, Faculty of Technology, University of Ibadan, Ibadan, 2010.

[4] S. Christos and S. Dimitrios, “Introduction to Artificial Neural Network,” Research Report, 2001.

[5] H. L. Hoffman, D. E. Lupfer, L. A. Kane and B. A. Jensen, “Distillation Column, Basic and Advance Controls Process Control, Instrument Engineer Handbook,” 3rd Edition, Butherworth Heinemann, Oxford, 1995.

[6] T. M. Gowrie and V. V. C. Reddy, “Load Forecasting by a Novel Technique Using ANN,” ARPN Journal of Engineering and Applied Sciences, Vol. 3, No. 1, 2008, pp. 19-25.

[7] J. W. Sea, M. Oh and T. H. Lee, “Design Optimization of Crude Oil Distillation,” Chemical Engineering Technology, Vol. 23, No. 2, 2000, pp. 157-164. doi:10.1002/(SICI)1521-4125(200002)23:2<157::AID-CEAT157>3.0.CO;2-C

[8] J. McCarthy, “Some Expert System Need Common Sense,” Stanford University, Stanford, 1984.

[9] D. B. Manley, “Waste Minimization through Improved Process Thermodynamics: Crude Oil Fractionation,” The University of Missouri, Rolla, 1993.

[10] E. I. Santana and R. J. Zemp, “Thermodynamic Analysis of a Crude-Oil Fractionating Process,” 4th Mercosur Congress on Process Systems Engineering, Vol. 21S, 2001, pp. 523-528.

[11] J. J. Yu, C. H. Zhou, S. Tan and C. C. Hang, “An On-line Soft-Sensor for Control and Optimization of Crude Distillation Column,” Research Institute of Industrial Process Control, Zhejiang University, Hangzhou, 1997.

[12] K. H. Bawazir and A. Zilouchian, “Application of Neural Networks in Oil Refineries,” Proceedings of 1996 IEEE International Conference on Neural Networks, New Orleans, 1999.

[13] L. C.-K. Liau, T. C.-K. Yangb and M. T. Tsaib, “Expert System of a Crude Oil Distillation Unit for Process Optimization Using Neural Networks,” Expert Systems with Applications, Vol. 26, No. 2, 2004, pp. 247-255. doi:10.1016/S0957-4174(03)00139-8

[14] A. Torgashov, “Nonlinear Process Model-Based Self-Optimizing Control of Complex Crude Distillation Column,” European Symposium on Computer Aided Process Engineering-11, Vol. 9, 2001, pp. 793-798.

[15] M. F. Khairiyah, K. Fakhri and L. D. Peter, “Connectionist Models of a Crude Oil Distillation Column for Real Time Optimisation,” Regional Symposium on Chemical Engineering 2002, Songkla, 2002.

[16] M. Gadalla, M. Jobson and M. Smith, “Optimisation of Existing Heat—Integrated Refinery Distillation Systems,” Ph.D. Thesis, UMIST, Manchester, 2002.

[17] E. O. Okeke and A. A. Osakwe-Akofe, “Optimization of a Refinery Crude Distillation Unit in the Context of Total Energy Requirement,” APACT03, 28-30 April 2003, NNPC R&D Division, Port Harcourt, 2003.

[18] P. Domijan and D. Kalpic, “Off-Line Energy Optimization Model for Crude Distillation Unit,” Ph.D. Thesis, Department of Applied Mathematics, Faculty of Electrical Engineering and Computing, University of Zagreb, Zagreb, 2004.

[19] J. J. Macías-Hernández, P. Angelov and X. Zhou, “Soft Sensor for Predicting Crude Oil Distillation Side Streams Using Evolving Takagi-Sugeno Fuzzy Models. Results Outlined,” Proceedings of 2nd International Symposium on Evolving Fuzzy Systems, 7-9 September 2008, Lake District, IEEE Press, 2008, pp. 214-220.

[20] B. A. Zalizawati, “Development of Multiple-Input Multiple-Output and Multiple-Input Single-Output Neural Network Models for Continuous Distillation Column,” M.Sc Thesis, School of Chemical, 2008.

[21] R. Kanthasamy, “Nonlinear Model Predictive Control of a Distillation Column Using Hammerstein Model and Nonlinear Autoregressive Model with Exogenous Input,” Ph.D. Thesis, Universiti Sains Malaysia, 2009.

[22] J. Haydary and T. Pavlik, “Steady-State and Dynamic Simulation of Crude Oil Distillation Using ASPEN Plus and ASPEN Dynamics,” Petroleum and Coal, Vol. 51, No. 2, 2009, p. 100.

[23] R. Smith, M. Jobson, L. Chen and S. Farrokhpanah, “Heat Integrated Distillation System Design,” Centre for Process Integration, School of Chemical Engineering and Analytical Science, The University of Manchester, 2010.

[24] Y. Kansha, A. Kishimoto and A. Tsutsumi, “Application of the Self-Heat Recuperation Technology to Crude Oil Distillation,” Collaborative Research Centre for Energy Engineering, Institute of Industrial Science, The University of Tokyo, Tokyo, 2011.

[25] K. Hornik, M. Stinchcombe and H. White, “Multilayer Feedforward Neural Networks Are Universal Approximators,” Neural Networks, Vol. 2, No. 5, 1989, pp. 359-366. doi:10.1016/0893-6080(89)90020-8

[26] D. Rumelhart and J. McClelland, “Parallel Distributed Processing,” MIT Press, Cambridge, 1986.

[27] G. Daniel, “Principles of Artificial Neural Networks,” Advanced Series in Circuits and Systems, Vol. 51, No. 2, 2007, pp. 100-109.