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Process Systems Engineering

Modeling and predictive control using fuzzy logic: Application for a polymerization system

  1. Nádson M. N. Lima1,*,
  2. Lamia Zuñiga Liñan1,
  3. Rubens Maciel Filho1,
  4. Maria R. Wolf Maciel1,
  5. Marcelo Embiruçu2,
  6. Filipe Grácio3

Article first published online: 9 NOV 2009

DOI: 10.1002/aic.12030

Issue

AIChE Journal

AIChE Journal

Volume 56, Issue 4, pages 965–978, April 2010

Additional Information

How to Cite

Lima, N. M. N., Liñan, L. Z., Filho, R. M., Maciel, M. R. W., Embiruçu, M. and Grácio, F. (2010), Modeling and predictive control using fuzzy logic: Application for a polymerization system. AIChE J., 56: 965–978. doi: 10.1002/aic.12030

Author Information

  1. 1

    Faculty of Chemical Engineering, Dept. of Chemical Processes, State University of Campinas—UNICAMP, University City, Campinas, São Paulo 13081-970, Brazil

  2. 2

    Polytechnique Institute, Federal University of Bahia—UFBA, Rua Professor Aristides Novis, Federação, Salvador, Bahia 40210-630, Brazil

  3. 3

    Center of Biological and Chemical Engineering, Biotechnology and Bioengineering Institute—IBB, Lisbon 1049-001, Portugal

*Faculty of Chemical Engineering, Dept. of Chemical Processes, State University of Campinas—UNICAMP, University City, Campinas, São Paulo 13081-970, Brazil

Publication History

  1. Issue published online: 12 MAR 2010
  2. Article first published online: 9 NOV 2009
  3. Manuscript Revised: 29 JUN 2009
  4. Manuscript Received: 2 DEC 2008

Funded by

  • FAPESP (Fundação de Amparo à Pesquisa do Estado de São Paulo)
  • CNPq (Conselho Nacional de Desenvolvimento Científico e Tecnológico)

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Keywords:

  • model predictive control;
  • fuzzy dynamic modeling;
  • model identification;
  • Takagi-Sugeno model;
  • copolymerization

Abstract

In this study, a predictive control system based on type Takagi-Sugeno fuzzy models was developed for a polymerization process. Such processes typically have a highly nonlinear dynamic behavior causing the performance of controllers based on conventional internal models to be poor or to require considerable effort in controller tuning. The copolymerization of methyl methacrylate with vinyl acetate was considered for analysis of the performance of the proposed control system. A nonlinear mathematical model which describes the reaction plant was used for data generation and implementation of the controller. The modeling using the fuzzy approach showed an excellent capacity for output prediction as a function of dynamic data input. The performance of the projected control system and dynamic matrix control for regulatory and servo problems were compared and the obtained results showed that the control system design is robust, of simple implementation and provides a better response than conventional predictive control. © 2009 American Institute of Chemical Engineers AIChE J, 2010

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