Control Of Polymerization Reactor Research Articles

A survey of advanced control of polymerization reactors

AbstractA survey of the most recent papers regarding the advanced control of polymerization reactors is carried out. Special attention is focused on optimal control theory, nonlinear control, adaptive control, and predictive control. A review is also performed in related areas, such as optimization and state estimation in polymerization systems. It is shown that there is a huge gap between industry and research practices. Actual implementation of advanced control theory in the polymerization area requires the improvement of measurement and state estimation techniques.

Control of Polymerization Reactors By F. Joseph Schork, Pradeep B. Deshpande, and Kenneth W. Leffew, Marcel Dekker, 1993, 376 pp., $145.00.

Control of Polymerization Reactors <i>By F. Joseph Schork, Pradeep B. Deshpande, and Kenneth W. Leffew, Marcel Dekker, 1993, 376 pp., $145.00</i>.

Control of Polymerization Reactors

Control of Polymerization Reactors

205 Application of Fuzzy logic in the control of polymerization reactors

205 Application of Fuzzy logic in the control of polymerization reactors

157 On-line estimation and control of polymerization reactors

157 On-line estimation and control of polymerization reactors

138 Modeling and control of polymerization reactors

138 Modeling and control of polymerization reactors

Application of fuzzy logic in the control of polymerization reactors

Polymer reactors are ideal candidates for the application of fuzzy control. Many polymerization reactions are difficult to model, process measurements are often only available from laboratory analysis at infrequent time intervals and trace impurities can have a marked effect on the reaction. All these factors are manifested in changing polymer properties, which makes control, using a conventional approach, difficult. Over the years, however, process operators have developed the ability to control the reactors under varying conditions. This article outlines how this experience was used in the development of a fuzzy control strategy, and the manner in which feedforward control was incorporated into the design. It also addresses the problem of tuning fuzzy controllers and describes some of the implementation difficulties.

Modeling and Control of Polymerization Reactors

The current state and key issues in the modeling and control of polymerization reactors are surveyed. The physical phenomena, types of reactor models, sensor hardware, process monitoring strategies, critical control problems, and control system design strategies are among the issues discussed. Extensive references are provided for further reading.

On-Line Estimation and Control of Polymerization Reactors

Controlling a batch polymerization reactor requires stable temperature control and precise polymer property control. The exothermicity of polymerization reactions and reactor fouling pose a challenging reactor temperature control problem. In this work, an extended Kalman filter is used to estimate time varying reactor heat transfer coefficient and polymer molecular weight parameters to achieve stable temperature control and accurate molecular weight control. Using an estimate of the overall heat transfer coefficient, the jacket temperature set point is automatically adjusted to prevent reactor temperature overshoot during the initial heat-up stage. Following heat-up, the polymer molecular weight is controlled by manipulating the reactor temperature.

Constrained optimal batch polymerization reactor control

AbstractThe theory of optimal control is used to analyze the performance of a batch PMMA (poly(methylmethacrylate)) polymerization reactor. Optimal dynamic profiles of temperature, initiator feed rate, and initiator concentration in the reactor are generated in order for specified conversion of monomer, number molecular weight, and polydispersity of the final product to be obtained. Based on tae physical limitations of the system, some restrictions are imposed to the control variable variations. The application of Pontryagin's Minimum Principle leads to a mixed initial/final value problem, which is solved by discretizing the control law in the state‐space, with the usage of a first order holder. A gradient method is used to minimize the Hamiltonian. The simulation results show that the gel‐effect equation and restrictions imposed on the system are of primary importance to the analysis of the reactor performance.

Continuous solution polymerization reactor control. 2. Estimation and nonlinear reference control during methyl methacrylate polymerization

ADVERTISEMENT RETURN TO ISSUEPREVArticleNEXTContinuous solution polymerization reactor control. 2. Estimation and nonlinear reference control during methyl methacrylate polymerizationDerinola K. Adebekun and F. Joseph SchorkCite this: Ind. Eng. Chem. Res. 1989, 28, 12, 1846–1861Publication Date (Print):December 1, 1989Publication History Published online1 May 2002Published inissue 1 December 1989https://doi.org/10.1021/ie00096a017RIGHTS & PERMISSIONSArticle Views224Altmetric-Citations50LEARN ABOUT THESE METRICSArticle Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated. Share Add toView InAdd Full Text with ReferenceAdd Description ExportRISCitationCitation and abstractCitation and referencesMore Options Share onFacebookTwitterWechatLinked InReddit PDF (1 MB) Get e-Alerts Get e-Alerts

Continuous solution polymerization reactor control. 1. Nonlinear reference control of methyl methacrylate polymerization

ADVERTISEMENT RETURN TO ISSUEPREVArticleNEXTContinuous solution polymerization reactor control. 1. Nonlinear reference control of methyl methacrylate polymerizationDerinola K. Adebekun and F. Joseph SchorkCite this: Ind. Eng. Chem. Res. 1989, 28, 9, 1308–1324Publication Date (Print):September 1, 1989Publication History Published online1 May 2002Published inissue 1 September 1989https://doi.org/10.1021/ie00093a008RIGHTS & PERMISSIONSArticle Views222Altmetric-Citations35LEARN ABOUT THESE METRICSArticle Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated. Share Add toView InAdd Full Text with ReferenceAdd Description ExportRISCitationCitation and abstractCitation and referencesMore Options Share onFacebookTwitterWechatLinked InReddit PDF (1 MB) Get e-Alerts Get e-Alerts

Estimation and control in polymerization reactors. A review

AbstractThe control of polymerization reactors is particularly arduous for several reasons; (a) difficulty in specification of the control objectives; (b) high exothermicities and viscosities involved: (c) complicated process dynamics: and (d) problems with measurement of the polymer structure. Computer control has now simplified many tasks such as sequential operations of batch reactors; but no less important, it has made feasible the implementation of elaborate state estimation and control algorithms. The tendency in the polymerization industry and in current research centers is centered on producing ‘tailor‐made’ polymers from the view of its microscopic and/or macroscopic structures. To this end, several solutions have been proposed. For example, in the ‘chemical approach’, open loop methods have been developed based on the detailed dynamic models of the processes. Any control technique requires a knowledge of the process to be controlled through mathematical models. These models may be developed either from detailed mass and energy balances, or through empirical input‐output or “black‐box” techniques. The most promising control techniques are probably optimal control, adaptive control, and their combinations. Optimal control is powerful because it utilizes directly the detailed non‐linear plant model. Adaptive control developed for linear plants has already proven satisfactory, in spite of the highly nonlinear nature of the polymerizations. Undoubtedly, improved solutions will be obtained when this technique is extended to non‐linear systems.

Control of Polymerization Reactors

Control of Polymerization Reactors

Polynumerization reactor control

The principal difficulties in achieving good control of polymerization reactors are related to inadequate on-line measurement, a lack of understanding of the dynamics of the process, the highly sensitive and nonlinear behavior of these reactors, and the lack of well-developed techniques for the control of nonlinear processes. Some illustrations of these problems and a discussion of potential techniques for overcoming some of these difficulties are provided.

Real-time estimation of the chain length distribution in a polymerization reactor—II. comparison of estimated and measured distribution functions

In Part I of this series (1985, Chem. Engng Sci. 40, 1891) the chain length distribution of polystyrene produced in a batch stirred tank reactor was estimated. The estimation procedure applied was based on a mathematical process model and the measured signals of temperature and refractive index. In the present paper these estimated distribution functions are compared to the measured chain length distributions obtained from a gel permeation chromatograph. The estimated distributions compare favourably with the measurements. The state estimator can therefore be applied in the wider context of supervision and control of polymerization reactors.

On-Line Measurement and Control of a Polymerization Reactor

A novel experimental reactor system has been designed to study a variety of problems related to on-line measurement and control of batch polymerization reactors. A number of measuring devices such as densitometer, torquemeter, viscometer, gel permeation chromatograph (GPC) have been put on-line with a batch polymerization reactor and interfaced to a real time computer (Hewlett-Packard HP/1000) to monitor conversion and molecular weight during polymerization. A new feature of our setup is its sampling system which collects reactor samples for automatic injection into a GPC. Computer proBrams have been developed for automatic GPC data collection and subsequent processing to determine molecular weight averages. The overall objective of this project is to demonstrate the feasibility of on-line measurements and control of a batch polymerization process.

Control of Polymerization Reactors

The demand for polymers and polymer latexes having special properties and improved performance has led to a rapid increase in industrial and academic interest in advanced computer modelling and control of polymer reactors. This paper presents a survey of recent literature on the optimization and control of specific polymer and latex properties, including: particle size distributions, copolymer composition, molecular weights and branching frequencies. Mathematical models and on-line sensors which are of central importance to these methods are also reviewed.

The optimal control of polymerisation reactors

AbstractTwo separate but related problems are treated in this paper: (i) the optimal control policy for continuous stirred tank polymerization reactors; (ii) the optimal control program for batch polymerization reactors. The first problem concerns determining the temperature and initiator control policy which brings the reactor to the desired steady state while minimizing some objective functional (e.g. start‐up time, cost of control action, etc.). The second problem is concerned with finding the best temperature and initiator program so that the product from the batch reactor has the best possible molecular weight distribution.Both free radical polymerization and linear condensation polymerization examples are considered with molecular weight distribution moments being used to characterize the polymer. Kinetic parameters typical of styrene are used for the free radical case, and realistic parameters are chosen for the condensation examples. The techniques used can be immediately carried over to other polymerization systems, and hopefully generalizations about the character of the optimal policies for such new systems can be made by considering the policies found for the systems studied. The results of the study demonstrate some of the potential gains possible through supervisory computer control of polymerization reactors.