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:
A Two-Armed Bandit Collective for Hierarchical Examplar Based Mining of Frequent Itemsets with Applications to Intrusion Detection Read chapter Read first chapter

2014 | OriginalPaper | Chapter

Methods of Prediction Improvement in Efficient MPC Algorithms Based on Fuzzy Hammerstein Models

Author : Piotr M. Marusak

Published in: Transactions on Computational Collective Intelligence XIV

Publisher: Springer Berlin Heidelberg

Log in

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

search-config
loading …

Abstract

Two methods of prediction improvement in Model Predictive Control (MPC) algorithms utilizing fuzzy Hammerstein models are proposed in the paper. The first one consists in iterative adjustment of the prediction, the second one – in utilization of disturbance measurement. Though the methods can significantly improve control system operation, they modify the prediction in such a way that it is described by relatively simple analytical formulas. Thus, the prediction has such a form that the MPC algorithms using it are formulated as numerically efficient quadratic optimization problems. Efficiency of the MPC algorithms based on the prediction utilizing the proposed methods of improvement is demonstrated in the example control system of a nonlinear control plant with significant time delay.

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 Extended Learning Method for Designation of Co-operation
next chapter Visualization of Semantic Data Based on Selected Predicates
Literature
1.
Abonyi, J., Babuska, R., Botto, M.A., Szeifert, F., Nagy, L.: Identification and control of nonlinear systems using fuzzy Hammerstein models. Ind. Eng. Chem. Res. 39, 4302–4314 (2000)CrossRef
2.
Babuska, R., te Braake, H.A.B., van Can, H.J.L., Krijgsman, A.J., Verbruggen, H.B.: Comparison of intelligent control schemes for real-time pressure control. Control Eng. Pract. 4, 1585–1592 (1996)CrossRef
3.
Camacho, E.F., Bordons, C.: Model Predictive Control. Springer, London (1999)CrossRef
4.
Chang, F.C., Huang, H.C.: A refactoring method for cache-efficient swarm intelligence algorithms. Inf. Sci. 192, 39–49 (2012)CrossRef
5.
Fink, A., Fischer, M., Nelles, O., Isermann, R.: Supervision of nonlinear adaptive controllers based on fuzzy models. Control Eng. Pract. 8, 1093–1105 (2000)CrossRef
6.
Huo, H.-B., Zhu, X.-J., Hu, W.-Q., Tu, H.-Y., Li, J., Yang, J.: Nonlinear model predictive control of SOFC based on a Hammerstein model. J. Power Sources 185, 338–344 (2008)CrossRef
7.
Janczak, A.: Identification of Nonlinear Systems using Neural Networks and Polynomial Models: A Block-Oriented Approach. Springer, Heidelberg (2005)
8.
Jurado, F.: Predictive control of solid oxide fuel cells using fuzzy Hammerstein models. J. Power Sources 158, 245–253 (2006)CrossRef
9.
Maciejowski, J.M.: Predictive Control with Constraints. Prentice Hall, Harlow (2002)
10.
Marusak, P.: Advantages of an easy to design fuzzy predictive algorithm in control systems of nonlinear chemical reactors. App. Soft Comput. 9, 1111–1125 (2009)CrossRef
11.
Marusak, P.M.: Efficient model predictive control algorithm with fuzzy approximations of nonlinear models. In: Kolehmainen, M., Toivanen, P., Beliczynski, B. (eds.) ICANNGA 2009. LNCS, vol. 5495, pp. 448–457. Springer, Heidelberg (2009) CrossRef
12.
Marusak, P.M.: On prediction generation in efficient MPC algorithms based on fuzzy Hammerstein models. In: Rutkowski, L., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds.) ICAISC 2010, Part I. LNCS, vol. 6113, pp. 136–143. Springer, Heidelberg (2010) CrossRef
13.
Marusak, P.M.: Numerically efficient analytical MPC algorithm based on fuzzy Hammerstein models. In: Dobnikar, A., Lotrič, U., Šter, B. (eds.) ICANNGA 2011, Part II. LNCS, vol. 6594, pp. 177–185. Springer, Heidelberg (2011) CrossRef
14.
Marusak, P.M.: Advanced prediction method in efficient MPC algorithm based on fuzzy Hammerstein models. In: Jędrzejowicz, P., Nguyen, N.T., Hoang, K. (eds.) ICCCI 2011, Part I. LNCS, vol. 6922, pp. 193–202. Springer, Heidelberg (2011)
15.
Morari, M., Lee, J.H.: Model predictive control: past, present and future. Comput. Chem. Eng. 23, 667–682 (1999)CrossRef
16.
17.
Rossiter, J.A.: Model-Based Predictive Control. CRC Press, Boca Raton (2003)
18.
Takagi, T., Sugeno, M.: Fuzzy identification of systems and its application to modeling and control. IEEE Trans. Syst. Man Cybern. 15, 116–132 (1985)CrossRefMATH
19.
Tatjewski, P.: Advanced Control of Industrial Processes; Structures and Algorithms. Springer, London (2007)MATH
Metadata
Title
Methods of Prediction Improvement in Efficient MPC Algorithms Based on Fuzzy Hammerstein Models
Author
Piotr M. Marusak
Copyright Year
2014
Publisher
Springer Berlin Heidelberg
Book
Transactions on Computational Collective Intelligence XIV

Print ISBN: 978-3-662-44508-2

Electronic ISBN: 978-3-662-44509-9

Copyright Year: 2014

DOI
https://doi.org/10.1007/978-3-662-44509-9_8

Premium Partner

    Image Credits