Skip to main content
Disciplines
Automotive Business IT + Informatics Construction + Real Estate Electrical Engineering + Electronics Energy + Sustainability Insurance + Risk Finance + Banking Management + Leadership Marketing + Sales Mechanical Engineering + Materials
Events
DE
EN
Books
Journals
Topic Page
Marketing
Start single access now
Access for companies
EXTENDED SEARCH
Log in
Top
Published in:
Introduction Read chapter Read first chapter

2020 | OriginalPaper | Chapter

5. Parameter Identification and Optimization of Chemical Processes

Authors : Jili Tao, Ridong Zhang, Yong Zhu

Published in: DNA Computing Based Genetic Algorithm

Publisher: Springer Singapore

Log in

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

Because of the complex nonlinear characteristics of chemical processes, traditional numerical optimization algorithms generally cannot be used to solve the modeling and optimization problems. In this chapter, the estimation of model parameters for heavy oil thermal cracking is firstly solved by RNA-GA. Then, we use DNA-DHGA to solve the recipe optimization problem of gasoline blending with heavy nonlinear inequality constraints. DNA computing based GAs are efficient in solving the optimization problems in chemical processes.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

inform now
previous chapter DNA Computing Based Multi-objective Genetic Algorithm
next chapter GA-Based RBF Neural Network for Nonlinear SISO System
Appendix
Available only for authorised users
Literature
1.
Turton, R., R.C. Bailie, W.B. Whiting, et al. 2008. Analysis, synthesis and design of chemical processes. Pearson Education.
2.
Thompson, M.L., and M.A. Kramer. 1994. Modeling chemical processes using prior knowledge and neural networks. AIChE Journal 40 (8): 1328–1340.CrossRef
3.
Li, C., C. Yang, and H. Shan. 2007. Maximizing propylene yield by two-stage riser catalytic cracking of heavy oil. Industrial and Engineering Chemistry Research 46 (14): 4914–4920.CrossRef
4.
He, Y.L., and Q.X. Zhu. 2016. A novel robust regression model based on functional link least square (FLLS) and its application to modeling complex chemical processes. Chemical Engineering Science 153: 117–128.CrossRef
5.
Song, X., et al. 2003. Eugenic evolution strategy genetic algorithms for estimating parameters of heavy oil thermal cracking model. Journal of Chemical Engineering of Chinese Universities 17 (4): 411–417.
6.
Björck, Å. 1996. Numerical methods for least squares problems. Society for Industrial and Applied Mathematics.
7.
Murshudov, G.N., A.A. Vagin, and E.J. Dodson. 1997. Refinement of macromolecular structures by the maximum-likelihood method. Acta Crystallographica. Section D, Biological Crystallography 53 (3): 240–255.CrossRef
8.
Zhong, X., and S. Wang. 1998. On-line soft sensing for end point of naphtha based on neural network. Journal of Chemical Industry & Engineering 49 (2): 251–255.
9.
Tao, J., and N. Wang. 2007. DNA computing based RNA genetic algorithm with applications in parameter estimation of chemical engineering processes. Computers & Chemical Engineering 31 (12): 1602–1618.CrossRef
10.
Li, J., I.A. Karimi, and R. Srinivasan. 2010. Recipe determination and scheduling of gasoline blending operations. AIChE Journal 56 (2): 441–465.
11.
Pasadakis, N., V. Gaganis, and C. Foteinopoulos. 2006. Octane number prediction for gasoline blends. Fuel Processing Technology 87 (6): 505–509.CrossRef
12.
Litvinenko, V.I., et al. 2002. Application of genetic algorithm for optimization gasoline fractions blending compounding. In IEEE international conference on artificial intelligence systems.
13.
Zhao, X. 2010. Blending scheduling based on particle swarm optimization algorithm. In 2010 Chinese control and decision conference. IEEE.
14.
Pan, H., and L. Wang, 2006. Blending scheduling under uncertainty based on particle swarm optimization with hypothesis test. In 2006 international conference on intelligent computing, 109–120. Springer.
15.
Kirgina, M.V., et al. 2014. Computer program for optimizing compounding of high-octane gasoline. Chemistry Technology of Fuels Oils 50 (1): 17–27.CrossRef
16.
Sakhnevitch, B., et al. 2014. Complex system for gasoline blending maintenance. Procedia Chemistry 10: 289–296.CrossRef
17.
Shang, B., L. Jiao, and Z. Shang. 2007. The optimum control design for gasoline piping automatic blending. Automation in Petro-Chemical Industry 1: 22–24.
18.
Li, W., L. Shi, and C. Liang. 2009. Forecasting model of research octane number based on PSO-VB-LSSVM. Chinese Journal of Scientific Instrument 30 (2): 335–339.
19.
Zhang, J., X. Luo, and L. Yang. 2006. Dvelopment of online optimization system of gasoline blending. Computer Engineering and Applications 42 (33): 216–218.
20.
Tao, J., and N. Wang. 2008. DNA double helix based hybrid GA for the gasoline blending recipe optimization problem. Chemical Engineering and Technology 31 (3): 440–451.CrossRef
21.
Zhong, X., Q. Zhang, and S. Wang. 2001. Multivariable constrained generalized predictive control strategy for the FCCU main fractionator. Control Theory & Applications 18: 134–140.MATH
22.
Liu, Q. and Q. Kang. 1997. The DCS implementation of FCCU main fractionator tray 20 temperature feed forward control system. Automation in Refined and Chemical Industry 5: 29–32. (In Chinese).
23.
Zhang, Y., D. Monder, and J.F. Forbes. 2017. Real-time optimization under parametric uncertainty: a probability constrained approach. Journal of Process Control 12 (3): 373–389.CrossRef
24.
Zhao, X., Research on Refinery Production Scheduling Problems. 2005, Zhejiang University.
Metadata
Title
Parameter Identification and Optimization of Chemical Processes
Authors
Jili Tao
Ridong Zhang
Yong Zhu
Copyright Year
2020
Publisher
Springer Singapore
Book
DNA Computing Based Genetic Algorithm

Print ISBN: 978-981-15-5402-5

Electronic ISBN: 978-981-15-5403-2

Copyright Year: 2020

DOI
https://doi.org/10.1007/978-981-15-5403-2_5

Premium Partner

    Image Credits