Performance of Various Methods in Computing Optimal Control Policies

Murty, B. S. N.; Gangiah, K.; Husain, Ashghar

doi:10.1016/0300-9467(80)80030-x

Cited by 15 publications

(11 citation statements)

References 10 publications

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“…To maximize the amount of distillate of a specified concentration for a specified time (Converse and Gross, 1963;Keith and Brunet, 1971;Murty et al, 1980;Diwekar et al, 1987;Logsdon et al, 1990;Farhat et al, 1990).…”

Section: Previous Workmentioning

confidence: 99%

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

Diwekar

1992

AIChE Journal

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Section: Previous Workmentioning

confidence: 99%

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

Diwekar

1992

AIChE Journal

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“…1. Maximum distillate problem: collection of maximum amount of distillate with specified concentration in a prescribed final time (Converse and Gross, 1963;Keith and Brunet, 1971;Murty et al, 1980;Diwekar et al, 1987) 2. Minimum time problem: minimization of final distillation time to produce a given amount of distillate with specified concentration (Coward, 1967a, b;Robinson, 1969Robinson, , 1970Mayur and Jackson, 1971;Egly et al, 1979Egly et al, , 1983Hansen and Jorgensen, 1986;Mujtaba and Macchietto, 1988) 3.…”

Section: Previous Workmentioning

confidence: 99%

“…The liquid holdup is either generally neglected (Converse and Gross, 1963;Coward, 1967a, b;Robinson, 1969;Keith and Brunet, 1971;Gangiah and Husain, 1974;Kerkhof and Vissers, 1978;Murty et al, 1980;Hansen and Jorgensen, 1986;Diwekar et al, 1987;Diwekar et al, 1989) or considered only as binary mixtures (Mayur and Jackson, 1971).…”

Section: Previous Workmentioning

confidence: 99%

Optimization of multiple‐fraction batch distillation by nonlinear programming

et al. 1990

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Batch distillation processes are very attractive for the recent development of the chemical industry: multipurpose, flexible plants and fine chemistry. For many separations of high-added value products, even a modest change in operating conditions has a significant economic impact-there is an important challenge for optimizing such processes.Short-cut and dynamic models are the two classical approaches to the simulation of batch distillation columns. For problems without holdup, an intermediate procedure based on a decoupling method is validated.For a multifraction separation problem with fixed final time, the reflux policies for each period and the period switching times constitute the set of decision variables. For predefined reflux policies, we apply an engineering approach to the solution of a such constrained variational problem, based on its transformation into a nonlinear programming problem. In this computer-implementable algorithm, the gain in distillate for the optimal linear or exponential reflux policies is significant (about 1O0/o) compared with the optimal constant reflux policy.

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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%

“…Maximum Distillate Problem–where the amount of distillate of a specified concentration for a specified time 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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Performance of Various Methods in Computing Optimal Control Policies

Cited by 15 publications

References 10 publications

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

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

Optimization of multiple‐fraction batch distillation by nonlinear programming

Missing Components in Multicomponent Batch Distillation and Optimal Control

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