Polymer grade transition control using advanced real-time optimization software

Benamor, S.; Doyle, Francis J.; McFarlane, Randall C.

doi:10.1016/j.jprocont.2003.06.001

Cited by 49 publications

(33 citation statements)

References 32 publications

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“…The controlled variables z k are represented in a somewhat general fashion by some nonlinear function g(Á) of the states. Note that the setpoint input to the controller can be supplied either manually by operator intervention or automatically using a supervisory realtime optimization (RTO) layer [3].…”

Section: Controller Algorithmmentioning

confidence: 99%

“…The main advantage of MPC is that it provides a unified framework to handle systems that are potentially multivariable, nonsquare, and possess hard constraints on one or more process variables. Despite the tremendous success of LMPC in the chemical process industries, it is not recommended for systems which exhibit high degrees of process nonlinearity and/or which are required to function over a wide operating region [3]. In such cases, nonlinear model predictive control (NMPC) provides an intuitive solution which inherently takes the nonlinear dynamics into account in the controller algorithm.…”

Section: Introductionmentioning

confidence: 99%

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Nonlinear MPC of a multi-zone multi-feed LDPE autoclave reactor

Jacob

Dhib

2012

Journal of Industrial and Engineering Chemistry

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Section: Controller Algorithmmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Nonlinear MPC of a multi-zone multi-feed LDPE autoclave reactor

Jacob

Dhib

2012

Journal of Industrial and Engineering Chemistry

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“…For this reason, optimization of grade transition trajectories is of fundamental importance for improvement of product quality and maximization of economic benefits. [19,20] Generally, grade transition studies focus on the implementation of stable, safe, and fault-free operation trajectories intended to minimize the transition period, prevent off-spec production, and avoid plant shutdown. [21] To date, no controller reconfiguration scheme has been proposed in order to extend the plant operation to the entire range of product specifications when multiple catalysts are used at plant site.…”

Section: Introductionmentioning

confidence: 99%

Control of Bulk Propylene Polymerizations Operated with Multiple Catalysts through Controller Reconfiguration

Dutra

Feital

Skogestad

et al. 2013

Macromol. React. Eng.

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This paper presents a model to describe the dynamic behavior of bulk propylene polymerizations performed in a continuous reactor, assuming that three catalysts can be used. The model takes into account mass, energy, and statistical moment balances used to estimate the final polymer properties, including the melt index (MI) and extractables in xylene (XS). As the catalysts present different sensitivities to hydrogen, the proposed controller scheme considers that the MI control loop must be reconfigured in line and in real time when the catalysts are exchanged. Simulation results indicate that the reactor stability is maintained during specified production programs and that the desired final properties can be achieved satisfactorily. It is shown that control reconfiguration represents an alternative to overcome existing operation limits and recover operability when multiple catalysts are used at plant site.

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“…MPC benefits have been validated on polymerization reactors [6][7][8][9] by providing good results (i.e., satisfactory tracking performance, robustness, ability to suppress disturbances, and accuracy under real-time constraints) without significantly increasing computational complexity and effort [10][11][12][13][14][15]. Some recent works also deal with stability and faulttolerant design issues [16][17][18].…”

Section: Introductionmentioning

confidence: 99%

Advanced Control of a Continuous Solution Copolymerization Process

Lima

Liñan

Manenti

et al. 2011

International Journal of Chemical Engineering

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A model-based predictive control system is designed for a copolymerization reactor. These processes typically have such a high nonlinear dynamic behavior to make practically ineffective the conventional control techniques, still so widespread in process and polymer industries. A predictive controller is adopted in this work, given the success this family of controllers is having in many chemical processes and oil refineries, especially due to their possibility of including bounds on both manipulated and controlled variables. The solution copolymerization of methyl methacrylate with vinyl acetate in a continuous stirred tank reactor is considered as an industrial case study for the analysis of the predictive control robustness in the field of petrochemical and polymer production. Both regulatory and servo problems scenarios are considered to check tangible benefits deriving from modelbased predictive controller implementation.

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Polymer grade transition control using advanced real-time optimization software

Cited by 49 publications

References 32 publications

Nonlinear MPC of a multi-zone multi-feed LDPE autoclave reactor

Nonlinear MPC of a multi-zone multi-feed LDPE autoclave reactor

Control of Bulk Propylene Polymerizations Operated with Multiple Catalysts through Controller Reconfiguration

Advanced Control of a Continuous Solution Copolymerization Process

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