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Fuzzy Logic Modeling and Observers Applied to Estimate Compositions in Batch Distillation Columns

In: Distillation - Modelling, Simulation and Optimization

Author

Listed:
  • Mario Heras-Cervantes
  • Gerardo Marx Chavez-Campos
  • Hector J. Vergara-Hernandez
  • Adriana Tellez-Anguiano
  • Juan Anzurez-Marin
  • Elisa Espinosa-Juarez

Abstract

In this chapter, the analysis and design of a fuzzy observer based on a Takagi-Sugeno model of a batch distillation column are presented. The observer estimates the molar compositions and temperatures of the light component in the distillation column considering a binary mixture. This estimation aims to allow monitoring the physical variables in the process to improve the quality of the distillated product as well as to detect failures that could affect the system performance. The Takagi-Sugeno fuzzy model is based on eight linear subsystems determined by three premise variables: the opening percentage of the reflux valve and the liquid molar composition of the light element of the binary mixture in the boiler and in the condenser. The stability analysis and the observer gains are obtained by linear matrix inequalities (LMIs). The observer is validated by MATLAB® simulations using real data obtained from a distillation column to verify the observer's convergence and analyze its response under system disturbances.

Suggested Citation

  • Mario Heras-Cervantes & Gerardo Marx Chavez-Campos & Hector J. Vergara-Hernandez & Adriana Tellez-Anguiano & Juan Anzurez-Marin & Elisa Espinosa-Juarez, 2019. "Fuzzy Logic Modeling and Observers Applied to Estimate Compositions in Batch Distillation Columns," Chapters, in: Vilmar Steffen (ed.), Distillation - Modelling, Simulation and Optimization, IntechOpen.
    • Handle: RePEc:ito:pchaps:180189
    DOI: 10.5772/intechopen.83479
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    More about this item

    Keywords

    Takagi-Sugeno modeling; fuzzy observers; composition estimation; distillation column;
    All these keywords.

    JEL classification:

    • C60 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - General

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