Skip to main content
Fachgebiete
Automobil + Motoren Bauwesen + Immobilien Business IT + Informatik Elektrotechnik + Elektronik Energie + Nachhaltigkeit Finance + Banking Management + Führung Marketing + Vertrieb Maschinenbau + Werkstoffe Versicherung + Risiko
DE
EN
Themenseiten
Organisationspsychologie Projektmanagement Marketing Smart Manufacturing
Bücher
Zeitschriften
Weitere Formate
Podcasts Webinare Technik Webinare Wirtschaft Kongresse Veranstaltungskalender Awards
Jetzt Einzelzugang starten
Zugang für Unternehmen
Referenzkunden
MTZ-Fachkongress

Antriebe und Energiesysteme von morgen


Austausch von Automobil- und Energiewirtschaft

Am 14./15. Mai geht es in Chemnitz um die Mobilitätswende durch Elektro- und Wasserstofffahrzeuge.
Erweiterte Suche
Anmelden
nach oben
Erschienen in:
A Novel Color Image Encryption Algorithm Using Chaotic Map and Improved RC4 Kapitel lesen Erstes Kapitel lesen

2016 | OriginalPaper | Buchkapitel

Self-Organizing Migrating Algorithm Used for Model Predictive Control of Semi-batch Chemical Reactor

verfasst von : Lubomír Macků, David Sámek

Erschienen in: Automation Control Theory Perspectives in Intelligent Systems

Verlag: Springer International Publishing

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

The current availability of powerful computing technologies enables using of complex computational methods. One of such complex method is also the self-organizing migrating algorithm (SOMA). This algorithm can be used for solving of various optimization problems. It may be used even for such complex task, as the non-linear process control is. In this paper, the capability of using SOMA algorithm for the model predictive control (MPC) of semi-batch chemical reactor is studied. The MPC controller including self-organizing migrating algorithm (SOMA) is used for the optimization of the control sequence. The reactor itself is used in chromium recycling process in leather industry.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

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!

Jetzt informieren

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!

Jetzt informieren

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!

Jetzt informieren
Vorheriges Kapitel WiFi Multi Access Point Smart Home IoT Architecture
Nächstes Kapitel Model of Surveillance System Based on Sound Tracking
Literatur
1.
Kolomaznik, K., Adamek, M., Uhlirova, M.: Potential danger of chromium tanned wastes. In: HTE’07: Proceedings of the 5th IASME/WSEAS International Conference on Heat Transfer, Thermal Engineering and Environment, pp. 136–140, WSEAS, Athens, Greece (2007)
2.
Gazdos, F., Macku, L.: Analysis of a semi-batch reactor for control purposes. In: Proceedings of 22nd European Conference on Modelling and Simulation ECMS 2008, pp. 512–518. ECMS, Nicosia, Cyprus (2008)
3.
Coelho, L.S., Marianib, V.C.: An efficient cultural self-organizing migrating strategy for economic dispatch optimization with valve-point effect. Energy Convers. Manage. 51(12), 2580–2587 (2010)CrossRef
4.
Deep, K.: A self-organizing migrating genetic algorithm for constrained optimization. Appl. Math. Comput. 198(1), 237–250 (2008)
5.
Singh, D., Agrawal, S.: Log-logistic SOMA with quadratic approximation crossover. Paper presented at the International Conference on Computing, Communication and Automation, ICCCA 146–151, 2015 (2015)
6.
Nolle, L., Zelinka, I., Hopgood, A.A., Goodyear, A.: Comparison of an self-organizing migration algorithm with simulated annealing and differential evolution for automated waveform tuning. 36(10), 645–653 (2005)
7.
Luyben, W.L.: Chemical Reactor Design and Control. Wiley, Hoboken, NJ (2007)CrossRef
8.
Luyben, W.L.: Process Modeling, Simulation and Control for Chemical Engineers. McGraw-Hill, New York (1996)
9.
Caccavale, F., Iamarino, M., Pierri, F., Tufano, V.: Control and Monitoring of Chemical Batch Reactors. Springer, London (2011)
10.
Aguilar-Garnica, E., Garcia-Sandoval, J.P., Gonzalez-Alvarez, V.: PI controller design for a class of distributed parameter systems. Chem. Eng. Sci. 66(15), 4009–4019 (2001)
11.
Aguilar-Lopez, R., Martinez-Guerra, R., Maya-Yescas, R.: Temperature regulation via PI high-order sliding-mode controller design: application to a class of chemical reactor. Int. J. Chem. Reactor Eng. 7(1) 2009
12.
Vojtesek, J., Dostal, P.: Simulation of Adaptive Control Applied on Tubular Chemical Reactor. WSEAS Trans. Heat Mass Transf. 6(1), 1–10 (2011)
13.
Vojtesek, J., Dostal, P.: Two types of external linear models used for adaptive control of continuous stirred tank reactor. In: Proceedings of the 25th European Conference on Modelling and Simulation, pp. 501–507, ECMS, Krakow, Poland (2011)
14.
Leosirikul, A., Chilin, D., Liu, J., Davis, J.F., Christofides, P.D.: Monitoring and retuning of low-level PID control loops. Chem. Eng. Sci. 69(1), 287–295 (2012)CrossRef
15.
Du, W., Wu, X., Zhu, Q.: Direct design of a U-model-based generalized predictive controller for a class of nonlinear (polynomial) dynamic plants. Proc. Inst. Mech. Eng. Part I: J. Syst. Control Eng. 226(1), 27–42 (2012)
16.
Zhang, R., Xue, A., Wang, S.: Dynamic Modeling and Nonlinear Predictive Control Based on Partitioned Model and Nonlinear Optimization. Ind. Eng. Chem. Res. 50(13), 8110–8121 (2011)CrossRef
17.
Matusu, R., Zavacka, J., Prokop, R., Bakosova, M.: The Kronecker summation method for robust stabilization applied to a chemical reactor. J. Control Sci. Eng. 2011, article ID 273469 (2011)
18.
Hosen, M.A., Hussain, M.A., Mjalli, F.S.: Control of polystyrene batch reactors using neural network based model predictive control (NNMPC): An experimental investigation. Control Eng. Pract. 19(5), 454–467 (2011)CrossRef
19.
Rani, K.Y., Patwardhan, S.C.: Data-driven model based control of a multi-product semi-batch polymerization reactor. Chem. Eng. Res. Des. 85(10) (2007)
20.
Xaumiera, F., Le Lann, M.V., Cabassud, M., Casamatta, G.: Experimental application of nonlinear model predictive control: temperature control of an industrial semi-batch pilot-plant reactor. J. Process Control (2002). doi:10.​1016/​S0959-1524(01)00057-9CrossRef
21.
Hvala, N., Aller, F., Miteva, T., Kukanja, D.: Modelling, simulation and control of an industrial, semi-batch, emulsion-polymerization reactor. Comput. Chem. Eng. 35(10), 2066–2080 (2011)CrossRef
22.
Oravec, J., Bakošová, M.: Robust model-based predictive control of exothermic chemical reactor. Chem. Pap. 69(10), 1389–1394 (2015)CrossRef
23.
Dao, T.T.: Investigation on evolutionary computation techniques of a nonlinear system. Model. Simul. Eng. 2011, Article ID 496732 (2011)
24.
Zelinka, I., Davendra, D., Šenkeřík, R., Pluháček, M.: Investigation on evolutionary predictive control of chemical reactor. J. Appl. Logic 13(2), 156–166 (2015)CrossRef
25.
Bouhenchir, H., Cabassud, M., Le Lann, M.V.: Predictive functional control for the temperature control of a chemical batch reactor. Comp Chem Eng 30(6–7), 1141–1154 (2006)CrossRef
26.
Camacho, E.F., Bordons, C.: Model Predictive Control in the Process Industry. Springer, London (2004)MATH
27.
Zelinka, I.: SOMA—Self Organizing Migrating Algorithm. In: Onwubolu, G., Babu, B.V. (eds.) New Optimization Techniques in Engineering, pp. 167–217. Springer, London, UK (2004)CrossRef
28.
Metadaten
Titel
Self-Organizing Migrating Algorithm Used for Model Predictive Control of Semi-batch Chemical Reactor
verfasst von
Lubomír Macků
David Sámek
Copyright-Jahr
2016
Buch
Automation Control Theory Perspectives in Intelligent Systems

Print ISBN: 978-3-319-33387-8

Electronic ISBN: 978-3-319-33389-2

Copyright-Jahr: 2016

DOI
https://doi.org/10.1007/978-3-319-33389-2_25

Premium Partner

    Bildnachweise