DOI 10.17586/0021-3454-2017-60-9-904-911
UDC 658.5.012.7 УДК 658.5.012.7
COGNITIVE CONTROL SYSTEM FOR PRIMARY OIL REFINING
ITMO University, Saint Petersburg, 197101, Russian Federation; Associate professor
A. A. Musaev
Saint Petersburg National Research University of Information Technologies, Mechanics and Optics; student
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Abstract. Various ways of using cognitive technologies in modern control systems for primary oil refining process are considered. A general schematic of rectification column as an object under the control is demonstrated, an information about possible problems in monitoring and managing of the refining process is presented. Modern methods of cognitive control system design for primary oil refining are analyzed. A variety of options for building a cognitive control system are described, which can be combined with an existing system into a software-algorithmic complex.
Keywords: cognitive technologies, control systems, advanced control process, model predictive control, cognitive adviser, decision support system
References:
References:
- Anderson J.S. Proc. Advanced Control for the Process Industries, 9–11 Sept., Cambridge. 1992.
- Nikolaou M. Advances in Chemical Engineering, 2001, no. 26, рр. 131–204.
- Holsapple C.W., Whinston A.B. Decision Support Systems: A Knowledge-Based Approach, St. Paul, MN, West Publishing, 1996.
- Adriaans P., Zantings D. Data Mining, London, Addison-Wesley-Longman, 1996.
- Fingar P. Cognitive Computing. A Brief Guide for Game Changes, Florida, Meghan-Kiffer Press, 2015.
- Dean T.L. Artificial Intelligence: Theory and Practice, Utah, Addison-Wesley, 1995.
- Ginsberg M.L. Essentials of AI, NY, Morgan Kaufmann, 1993.
- Luger G., Stubblefield W. Artificial Intelligence: Structures and Strategies for Complex Problem Solving, San Francisco, CA, The Benjamin/Cummings Publishing, 1993.
- Poole D., Mackworth A., Goebel R. Computational Intelligence: A Logical Approach, Oxford University Press, 1998, 576 p.
- Pratt I. Artificial Intelligence, London, Macmillan, 1994.
- Stuart J., Russell S.J., Norvig P. Artificial Intelligence: A Modern Approach, New Jersey, Prentice Hall, 2009, 1152 p.
- Hand D.J., Mannila H., Smyth P. Principles of Data Mining, Cambridge, MA, MIT Press, 1997.
- Ian H., Eibe F., Hall M. Data Mining: Practical Machine Learning Tools and Techniques, NY, Morgan Kaufmann, 2011.
- Pyle D. Data Preparation for Data Mining, NY, Morgan Kaufmann, 1999.
- Weiss S.M., Indurkhya N. Predictive Data Mining, NY, Morgan Kaufmann, 1998.
- Berry M.J.A., Linoff G.S. Mastering Data Mining, NY, Wiley, 2000.
- Fayyad U.M., Piatetsky-Shapiro G., Smith P., Uthurusamy R. Advances in Knowledge Discovery and Data Mining, AAAI Press/MIT Press, 1996.
- Manyika J. Big data: The Next Frontier for Innovation, Competition, and Productivity, Texas, McKinsey Global Institute, 2011.
- Bamberger W., Isermann R. Automatica, 1978, no. 14, рр. 223–230.
- Garcia M.R., Vilas C., Santos L.O., Alonso A.A. J. Proc. Contr.,2012, no. 22(1), рр. 60–71.
- Mayne D., Rawlings R. Automatica, 2000, no. 6(36), рр.789–814.