On‐line nonlinear model‐based estimation and control of a polymer reactor

Mutha, Rajendra K.; Cluett, William R.; Penlidis, Alexander

doi:10.1002/aic.690431116

Cited by 70 publications

(50 citation statements)

References 23 publications

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“…of Chemical Engineering, Chemistry and Material Science, Polytechnic University, Brooklyn, NY 11201. Ž properties indirectly Mutha et al, 1997;Tsen et al, 1996; . Russel et al, 1998 .…”

Section: Introductionmentioning

confidence: 96%

Nonlinear model predictive control of end‐use properties in batch reactors

Valappil

Georgakis

2002

AIChE Journal

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“…of Chemical Engineering, Chemistry and Material Science, Polytechnic University, Brooklyn, NY 11201. Ž properties indirectly Mutha et al, 1997;Tsen et al, 1996; . Russel et al, 1998 .…”

Section: Introductionmentioning

confidence: 96%

Nonlinear model predictive control of end‐use properties in batch reactors

Valappil

Georgakis

2002

AIChE Journal

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“…This method can produce satisfactory process control schemes, but in most cases, there is no a priori guarantee of the convergence and stability of these algorithms. 8,11 The estimators proposed in earlier works [8][9][10] seem to present good convergence properties and robustness to both state and measurement noise. However, estimator tuning is not a trivial exercise.…”

Section: Introduction and Objectivesmentioning

confidence: 97%

Applications of Nonlinear Observers and Control: Improving Productivity and Control of Free Radical Solution Copolymerization

Hammouri

McKenna

Othman

1999

Ind. Eng. Chem. Res.

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A nonlinear state observer that uses the rate of heat generation due to chemical reaction for the real-time evaluation of key parameters during free radical solution copolymerization is presented. These parameters include the cumulative and instantaneous copolymer compositions, the overall and individual monomer conversions, and the overall termination rate constant associated with the reaction. The information thus obtained is used to control the cumulative copolymer composition and to maintain the productivity of a semibatch reactor for the solution copolymerization of butyl acrylate (BuA) and vinyl acetate (VAc) in ethyl acetate (EAc) at its highest possible level. Both the state and parameter estimation of this observer were then used for the nonlinear control of copolymer composition and optimal reactor productivity.

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“…In these cases, continuous estimates of these variables can be obtained from available frequent and/or infrequent (off-line) measurements, using a model of the process under consideration as well as the above-mentioned estimation algorithms. In recent years, the problem of multi-rate state and parameter estimation has received more attention, with emphasis on the extension of the EKF for processes with multi-rate/delayed measurements [15,16,17,18,19,20]. Multi-rate variables estimation allows for using infrequently available measurements in state and parameter estimation, leading to a considerable improvement in the accuracy of the resulting estimates.…”

Section: Introductionmentioning

confidence: 99%

Estimation of multiple biomass growth rates and biomass concentration in a class of bioprocesses

Lubenova

Rocha

Ferreira

2003

Bioprocess and Biosystems Engineering

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In this paper, an approach to the estimation of multiple biomass growth rates and biomass concentration is proposed for a class of aerobic bioprocesses characterized by on-line measurements of dissolved oxygen and carbon dioxide concentrations, as well as off-line measurements of biomass concentration. The approach is based on adaptive observer theory and includes two steps. In the first step, an adaptive estimator of two out of three biomass growth rates is designed. In the second step, the third biomass growth rate and the biomass concentration are estimated, using two different adaptive estimators. One of them is based on on-line measurements of dissolved oxygen concentration and off-line measurement of biomass concentrations, while the other needs only on-line measurements of the carbon dioxide concentration. Simulations demonstrated good performance of the proposed estimators under continuous and batch-fed conditions.

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On‐line nonlinear model‐based estimation and control of a polymer reactor

Abstract: Polymer reactor control problems often lack fiequent measurements of polymer properties, while

Cited by 70 publications

References 23 publications

Nonlinear model predictive control of end‐use properties in batch reactors

Nonlinear model predictive control of end‐use properties in batch reactors

Applications of Nonlinear Observers and Control: Improving Productivity and Control of Free Radical Solution Copolymerization

Estimation of multiple biomass growth rates and biomass concentration in a class of bioprocesses

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