Operability and Control in Process Synthesis and Design

Walsh, Stephen; Perkins, John D.

doi:10.1016/s0065-2377(08)60205-7

Cited by 21 publications

(20 citation statements)

References 22 publications

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“…Methods to solve problems 11 and 12 have been proposed in the literature [12,15,16,19,37,38]. Problem 12 is a bilevel problem.…”

Section: Solution Methods For Robust Optimal Control Problemsmentioning

confidence: 99%

“…The goal in their formulation is to design a process such that feasible operation is guaranteed at steady state operation for a set of uncertain parameters that may be encountered during operation. This approach was extended to continuous processes modelled by differential equations in [16] and [17]. In [18] a design methodology was proposed which computes optimal pro®les based on the probability distribution of the uncertain parameters.…”

Section: Optimal Control Of Fed Batch Fermentersmentioning

confidence: 99%

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Robust operation of fed batch fermenters

Kuhlmann

Bogle

Chalabi

1998

Bioprocess Engineering

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Optimisation of fed batch fermenters can substantially increase the pro®tability of these processes. Optimal control of a fed batch fermenter is usually based on a nominal process model. Parameter uncertainties are not taken into account. Simulation studies show that results obtained with ®xed nominal model parameters can be quite sensitive to the uncertainty in parameter values. This paper presents a method for obtaining robust optimal control pro®les in the presence of uncertainty in the model parameters. The proposed approach is illustrated with a case study. It is also shown that feedback controllers can reduce the effect of the uncertainties. IntroductionThe outcome of a fed batch fermentation depends on variables like fermentation time, feed rate pro®le, substrate concentration in the feed, oxygen concentration and pH in the broth amongst many others variables. Process engineers aim to operate a fermenter at optimum pro®t-ability subject to certain constraints. If a model of the process is available, it can be used to determine the optimal values or trajectories of the process variables. Since some of the optimisation variables are functions of time, the optimisation problem is essentially an optimal control problem. The solution to this problem identi®es the optimal time course of the process variables. However these pro®les can be quite sensitive to model uncertainties and the expected results cannot be achieved in practice. It can be shown through computer simulations that small changes in the parameters can yield results signi®cantly different from the expected performance. It is possible that a non-optimal control strategy performs better under real conditions than the optimal strategy. The optimisation should take model uncertainties into account in order to avoid bad performance under real conditions. This paper is divided into six parts including this Introduction and the Conclusion. In the second part we review several approaches to optimise fed batch processes, including those approaches which take model uncertainty into account. In the third part a general optimal control problem is formulated and the model uncertainty is introduced into the formulation. Solution methods to solve the optimal control problem are then reviewed. In the fourth part we propose a procedure to compute optimal control pro®les for fed batch fermenters taking the effects of model uncertainty into account. In the ®fth part, we apply the procedure to optimise a cell producing fed batch fermenter. Optimal control of fed batch fermentersOptimal control of fed batch fermentation has been widely studied and different approaches for the solution of these problems have been proposed. In [1] the feed rate was used as a control variable and an analytic expression for the switching times between bang-bang control intervals and singular arcs was derived. For the singular arcs, a feedback law for the feed rate was obtained. General characteristics for the optimal feed rate pro®les for different classes of fed batch fermentations were p...

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“…Methods to solve problems 11 and 12 have been proposed in the literature [12,15,16,19,37,38]. Problem 12 is a bilevel problem.…”

Section: Solution Methods For Robust Optimal Control Problemsmentioning

confidence: 99%

Section: Optimal Control Of Fed Batch Fermentersmentioning

confidence: 99%

Robust operation of fed batch fermenters

Kuhlmann

Bogle

Chalabi

1998

Bioprocess Engineering

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“…Design methods have been based on controllability and operability considerations as well as economic considerations 160], [239] and [216]. Frequency domain analysis and robustness analysis can also provide useful insight [216] and [231].…”

Section: Selection Of Control Structurementioning

confidence: 99%

“…It is important that various aspects of the plantwide control problem be considered during the process design itself [68], [175], [239] and [251]. The relation between process design and control can be succinctly summarized by the following quotation: "In the application of automatic controllers, it is important to realize that controller and process form a unit; credit or discredit for results obtained are attributable to one as much as the other.…”

Section: Selection Of Control Structurementioning

confidence: 99%

A Perspective on Advanced Strategies for Process Control (Revisited)

Seborg

1999

Advances in Control

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Summary. Th is paper provides a personal perspective on the current status of advanced process control. First, process control strategies are classified according to the extent to which they have been applied in industry. Then important new developments in information technology and plant automation are summarized. Prominent advanced process control methods are critiqued with emphasis placed on key issues and unresolved research problems. Finally, recent developments in an important related field, process monitoring, are reviewed.

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“…Walsh and Perkins [16] and Bahri, etc. [17] indicate that often this assumption is not satisfied in action. There are difficulties involved in real-time measurement of the concentrations of some substances.…”

Section: Introductionmentioning

confidence: 99%

Process Optimization under Insufficient Experimental Information in the Phase of Service

Volin

Ostrovskii

2005

Autom Remote Control

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The existing methods of process optimization under uncertain initial information are based on the assumption that in the phase of service known are the exact values of all parameters, which in the phase of design were regarded as partially uncertain. This assumption is too rigid and in practice often is not true. The paper presented new flexibility conditions and a new two-phase problem of optimization with the assumption that in the phase of service the precise values are known only for part of the uncertain parameters. An algorithm was developed to solve the two-phase problem for the case of insufficient experimental information in the process service phase.

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Operability and Control in Process Synthesis and Design

Cited by 21 publications

References 22 publications

Robust operation of fed batch fermenters

Robust operation of fed batch fermenters

A Perspective on Advanced Strategies for Process Control (Revisited)

Process Optimization under Insufficient Experimental Information in the Phase of Service

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