A Closed‐Loop Control Strategy for Producing Nitrile Rubber of Uniform Chemical Composition in a Semibatch Reactor: A Simulation Study

Abstract

To improve the quality of industrial nitrile rubbers, the copolymer chemical composition, pA(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 pA(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 pA(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 pA(t) in spite of structural and parametric uncertainties, while other quality variables remained practically unaffected.

An Adaptive Soft Sensor for On‐Line Monitoring the Mass Conversion in the Emulsion Copolymerization of the Continuous SBR Process

“…For example, an online sensor based on an artificial neural network (ANN) model was developed for estimating and controlling quality variables in the semibatch Nitrile rubber process. [ 3 ] Also, an online sensor based on ANN proved useful for the online estimation of production and quality variables in the continuous SBR process. [ 4 ]…”

“…For example, an online sensor based on an artificial neural network (ANN) model was developed for estimating and controlling quality variables in the semibatch Nitrile rubber process. [3] Also, an online sensor based on ANN proved useful for the online estimation of production and quality variables in the continuous SBR process. [4] A soft sensor (SS) is basically a mathematical model that allows estimating the value of an unmeasured variable from one or more known or online measured process variables.…”

Inferential Control of a Distillation Column through the Successive Update of the Soft-sensor and Control Algorithm

“…Most studies on inferential control have not considered the problems mentioned above, nor have they clearly specied the operating conditions under which the model construction data was obtained (Abusnina et al, 2014;Jiang et al, 2015;Bosca et al, 2016;Cao et al, 2017;Escalante-Sánchez et al, 2018;Jana and Banerjee, 2018;Guan et al, 2019). In other studies, the model construction data were collected under impractical conditions (Pannocchia and Brambilla, 2003;Bahar and Özgen, 2010;Vijaya Raghavan et al, 2011;Chiewchanchairat et al, 2015;Sakhre et al, 2016;Bidar et al, 2018;Clementi et al, 2018;Qian et al, 2019). Some authors have obtained the data used for model construction from plant operations without a control system (Pannocchia and Brambilla, 2003;Bahar and Özgen, 2010;Vijaya Raghavan et al, 2011;Chiewchanchairat et al, 2015;Sakhre et al, 2016).…”

“…Bidar et al (2018) frequently changed the setpoint when gathering the model construction data. Clementi et al (2018) conducted control simulations, where di cult-to-measure variables were controlled in real time, to obtain data for the model construction.…”

Mathematical Modeling of the Production of Elastomers by Emulsion Polymerization in Trains of Continuous Reactors

“…Notice that none of the previous cited works addressed continuous NBR production processes; it was only in the works of Minari et al [25,26] that the Vega et al model was extended to the case of a train of CSTRs for NBR production to study the effect of intermediate feed streams of chain transfer agents (CTAs) and AN on the polymer quality [25] and to reduce transients during grade transitions [26]. More recently, the model of Vega et al was used to evaluate a closed-loop control strategy to produce the NBR of uniform copolymer composition in a semibatch reactor [27].…”