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A Closed‐Loop Control Strategy for Producing Nitrile Rubber of Uniform Chemical Composition in a Semibatch Reactor: A Simulation Study
Author(s) -
Clementi Luis A.,
Suvire Romina B.,
Rossomando Francisco G.,
Vega Jorge R.
Publication year - 2018
Publication title -
macromolecular reaction engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.37
H-Index - 32
eISSN - 1862-8338
pISSN - 1862-832X
DOI - 10.1002/mren.201700054
Subject(s) - copolymer , parametric statistics , process (computing) , control theory (sociology) , natural rubber , nitrile rubber , nitrile , polymerization , constant (computer programming) , composition (language) , closed loop , computer science , control (management) , process engineering , materials science , mathematics , chemistry , engineering , control engineering , polymer , statistics , organic chemistry , linguistics , philosophy , artificial intelligence , programming language , composite material , operating system
To improve the quality of industrial nitrile rubbers, the copolymer chemical composition, p A ( t ), should ideally be kept constant along the reaction. This work proposes a closed‐loop control strategy for the semibatch operation of the reactor with the aim of regulating p A ( t ) within a reduced range of variability. The proposed strategy is evaluated by simulating a mathematical model of the process. To this effect, a simplified mathematical model of the reaction is first derived and then utilized to obtain a suboptimal control law and a soft‐sensor that estimates the polymerization rates. The suboptimal control law is compensated by adding a term proportional to errors in p A ( t ). The simulated example considers the production of the low‐composition AJLT grade, with the copolymerization reaction represented by a detailed mathematical model adjusted to an industrial plant. Due to the high performance of the soft‐sensor, the simulation results suggest that the proposed closed‐loop strategy is efficient to adequately regulate p A ( t ) in spite of structural and parametric uncertainties, while other quality variables remained practically unaffected.