Unified approach to solving optimal design‐control problems in batch distillation

Diwekar, Urmila M.

doi:10.1002/aic.690381007

Cited by 40 publications

(18 citation statements)

References 18 publications

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“…The purity requirement of the final product is commonly described by the following integral relation (Diwekar, 1992;Kim and Diwekar, 2001;Upreti, 2012):…”

Section: The Maximal Distillate Problem: An Optimal Control Formulationmentioning

confidence: 99%

“…(3.1)-(3.4), (7) are highly non-linear with respect to R. The corresponding optimal control problem is much more complicated and difficult to threat using the methods of optimal control and calculus of variations. Indeed, starting from the work of Converse and Gross (1963) and repeated later in Diwekar (1992), Kim and Diwekar (2001) and Diwekar (2014), only the singular type control was taken into account because the boundary conditions on the reflux ratio were not correctly treated in the application of the PMP.…”

Section: The Maximal Distillate Problem: An Optimal Control Formulationmentioning

confidence: 99%

“…Then Diwekar (1992) solved the optimal control problem of batch distillation by using a short-cut method based on a quasisteady-state model for each of the three problem categories listed by Mutjaba. They used this model in an algorithm combining Pontryagin's Maximum Principle and non-linear problem techniques.…”

Section: Introductionmentioning

confidence: 99%

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Cyclic operation as optimal control reflux policy of binary mixture batch distillation

Stojković

Gerbaud

Shcherbakova

2018

Computers & Chemical Engineering

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OATAO is an open access repository that collects the work of Toulouse researchers and makes it freely available over the web where possible. This is an author-deposited version published in: http://oatao. b s t r a c tWe revisit the maximum distillate optimal control problem of batch distillation of non-ideal binary zeotropic mixtures. The direct method with full discretization is used. The problem formulation is based on full column dynamics and the distillate flow rate is used as control variable instead of the reflux. The purity constraint is handled as a new state variable, the purity deviation. Literature simulations showed that the cyclic reflux policy (bang-bang type control) performs better than variable reflux (singular type control) or constant reflux policy for small amount of light product in the load. For the first time, a cyclic reflux policy is found as the optimal control solution. The results are confirmed by rigorous simulation of the batch distillation, as the cyclic policy improves by 13% the product recovery over the variable reflux policy. Influence of the relative volatility, vapour flow rate, plate hold-up and initial load is discussed.

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“…The purity requirement of the final product is commonly described by the following integral relation (Diwekar, 1992;Kim and Diwekar, 2001;Upreti, 2012):…”

Section: The Maximal Distillate Problem: An Optimal Control Formulationmentioning

confidence: 99%

Section: The Maximal Distillate Problem: An Optimal Control Formulationmentioning

confidence: 99%

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Cyclic operation as optimal control reflux policy of binary mixture batch distillation

Stojković

Gerbaud

Shcherbakova

2018

Computers & Chemical Engineering

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“…The optimization problems in batch distillation mostly involve optimal control problem where the time-dependent reflux profile is determined by optimizing some performance index. These problems are described below. Maximum Distillate Problem–where the amount of distillate of a specified concentration for a specified time is maximized − Thermodynamic Efficiency Problem–where the thermodynamic efficiency for a specified concentration of distillate at a specified time is maximized − Minimum Time Problem–where the batch time needed to produce a prescribed amount of distillate of a specified concentration is minimized − , Maximum Profit Problem–where a profit function for a specified concentration of distillate is maximized ,,, …”

Section: Introductionmentioning

confidence: 99%

Missing Components in Multicomponent Batch Distillation and Optimal Control

Diwekar

Rivier

2019

Ind. Eng. Chem. Res.

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Batch distillation is a commonly used unit operation in specialty chemicals. In order to maximize profitability and improve separations using a batch distillation column, optimal reflux operation can be used. The mathematical and numerical complexities of the optimal control problem get worse when uncertainty is present in the formulation. However, in the specialty chemical industry, thermodynamic properties of not all chemical components of a mixture to be separated are known. In reality, these components are treated as missing components and their composition is merged with known components. These uncertainties in the problem formulation can result in suboptimal solutions. In this work, we are providing a new approach to solve this problem. We use Ito processes and stochastic maximum principle for the formulation of the resulting stochastic optimal control problem. This algorithm is implemented in the MultiBatchDS batch distillation process simulator. Finally, a numerical case study derived from a real-world batch distillation separation problem encountered at Firmenich is presented to show the scope and application of the proposed approach.

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“…and Gross, 1963;Diwekar et al, 1987;Farhat et al 1990;Diwekar, 1992;Logsdon and Biegler, 1993;Zavala-Loría et al, 2006;ZavalaLoría and Coronado-Velásco, 2008); Minimum time problem: To minimize the operating time necessary to produce a certain amount of distillate that meets a specified concentration of the most volatile key component (Coward, 1967;Robinson, 1970;Mayur and Jackson, 1971;Hansen and Jorgensen, 1986;Mujtaba and Macchieto, 1988;Diwekar, 1992); Problem of maximum profit: To maximize a profit function for a specified concentration of product (Kerkhof and Vissers, 1978;Logsdon at al., 1990;Diwekar, 1992); Problem of minimum energy: Energy requirements are minimized to produce a certain amount of distillate to meet a specified concentration of the most volatile key component (Furlonge et al, 1999;Mukherjee et al, 2001); Maximum thermodynamic efficiency problem: To maximize the thermodynamic efficiency of the process in a fixed time to produce a quantity of distillate complying with a specified concentration of the most volatile key component (Zavala-Loría, 2004;Zavala-Loría and Coronado-Velásco, 2008).…”

Section: Introductionmentioning

confidence: 99%

Maximum thermodynamic efficiency problem in batch distillation

Loría

Ruiz-Marín

Coronado-Velasco

2011

Braz. J. Chem. Eng.

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-A dynamic batch distillation study of the non-ideal mixture Ethanol-Water is presented. The objective of the study was to calculate an average thermodynamic efficiency of the process under an optimal constant reflux policy and the objective function includes a given production time in order to obtain the desired product quality (measured as the average mole fraction of the accumulated product). An expression for computing the thermodynamic efficiency is presented. The simulation of the column uses a mathematical model considering the complete dynamics of the operation and the problem of optimal control resulting in a non-linear programming problem. A dynamic optimization technique based on a SQP method was used to solve the problem. The average thermodynamic efficiency for the separation process under the conditions presented was 37.95%.

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Unified approach to solving optimal design‐control problems in batch distillation

Cited by 40 publications

References 18 publications

Cyclic operation as optimal control reflux policy of binary mixture batch distillation

Cyclic operation as optimal control reflux policy of binary mixture batch distillation

Missing Components in Multicomponent Batch Distillation and Optimal Control

Maximum thermodynamic efficiency problem in batch distillation

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