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THE DEVELOPMENT AND EXPERIMENTAL TESTING OF A FUZZY CONTROL SYSTEM FOR BATCH DISTILLATION
Author(s) -
Ana Maria Frattini Fileti,
R.D. Pereira Filho,
João Alexandre Ferreira da Rocha Pereira
Publication year - 2002
Publication title -
brazilian journal of chemical engineering/brazilian journal of chemical engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.313
H-Index - 52
eISSN - 1678-4383
pISSN - 0104-6632
DOI - 10.1590/s0104-66322002000100001
Subject(s) - fuzzy logic , fuzzy control system , fractionating column , computer science , control theory (sociology) , overhead (engineering) , control engineering , distillation , engineering , control (management) , artificial intelligence , chemistry , organic chemistry , operating system
The present work describes the development and implementation of fuzzy control algorithms in order to control on-line the overhead product composition of a batch distillation column. Firstly, the influence of design parameters was evaluated through computational simulations and then the algorithms were experimentally tested by monitoring a pilot column. Binary mixtures of n-hexane/n-heptane were distilled. Temperature measurements and vapor-liquid equilibrium data are the basis for the inference of overhead and bottom compositions. Two different operational strategies were used for the experimental runs: constant overhead product composition and previously determined set-point trajectory. Using the first strategy, the performance of the fuzzy controllers is compared to the performance of conventional feedback digital controllers. Experimental results show that fuzzy control presents a better performance than the conventional digital feedback control and also that fuzzy controllers were able to deal successfully with variable set-point strategy, albeit using constant design parameter values. Under conventional control, the average reflux rate implemented was higher than the average reflux rate implemented with fuzzy algorithms. Consequently, the process becomes less time- and energy-consuming under fuzzy control. Since fuzzy methodology is a promising new way of looking at process control problems and their solutions, the results of this work could provide control system designers with a better evaluation of the potential worth of fuzzy control

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