Distillation Control Strategies

The strategy of distillation control is open to many creative approaches because there are five or six main variables to manipulate and many possibilities for cascade, feed-forward ratios, and model-based computer control as well as conventional feedback control. 

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Understand the four basic distillation control strategies... 

Tolliver and McCune described four alternative material balance control schemes for distillation columns. Each scheme manipulates a different variable to control a temperature point in the column, that is, the D/F ratio, and this provides a structure for categorizing distillation control strategies (Table 5.1). There can be a number of variations of the four basic control schemes. 

A distillation column provides a good example of multiple input/multiple output (MIMO) control and illustrates well the qualitative methodology involved in determining a suitable control strategy for a process. The first requirement is to decide the primary objective of the process, i.e. what is its principal purpose Let us suppose that, for the column shown in Fig. 7.9, it is required to produce an overhead product D of a particular specification xD without attempting to control... 

Optimization and vacuum control strategies (a) minimizing (floating) pressure by maximizing coolant valve opening, (b) floating pressure control of partial condenser with vapor distillate, (c) floating pressure control when the distillate is both vapor and liquid. 

The advanced process control strategies that are most applicable to the optimization of the distillation process are usually based on white-box modeling, where the theoretical dynamic models are derived on the basis of the mass, energy, and momentum balances of this well-understood process. Although the optimization techniques described here can improve productivity and profitability by 25%, this goal will only be achieved if the distillation process is treated as a single and integrated unit operation and the variables, such as flows, levels, pressures, etc., become only constraints, and the controlled and optimized variables are productivity and profitability. 

A two-level hybrid control strategy for the start-up of a coupled distillation plant, 2003. 

Cuille and Reklaitis (1986) and Albet et al. (1991) used similar model to simulate batch reactive distillation process. Egly et al. (1979), Reuter et al. (1989), Mujtaba (1989) and Mujtaba and Macchietto (1992, 1997) used a modified version of this model based on constant molar holdup in their studies. Sorensen and Skogestad (1996c), Sorensen et al. (1996b), Balasubramhanya and Doyle III (2000) used simple models for studying control strategies in batch reactive distillation. 

An alternative control strategy fixes the reactor-inlet toluene flow rate [16]. Fresh toluene is fed into the condenser drum of the last distillation column, on level control. Production-rate changes can be achieved by changing the setpoint of the toluene reactor-inlet flow, or the setpoint of the reactor-inlet temperature controller. When this control structure is used, the whole range of conversion becomes stable. Drawing of this control structure is left as an exercise to the reader. 

In Chaps. 4 and 6 we discuss specific control issues for chemical reactors and distillation columns. We shall then have much more to say about the important concepts of dominant variables and partial control. Much of the material in those chapters centers on the control of the units individually. However, we also try to show how plantwide control considerations may sometimes alter the control strategy for the unit from what we would normally have in an isolated system. 

For example, suppose that the distillate flowrate from a distillation column is large compared to the reflux. We normally would use distillate to control level in the reflux drum. But suppose the distillate recycles back to the reactor and so we want to control its flow. What manipulator should we use to control reflux drum level We could potentially use condenser cooling rate or reboiler heat input. Either choice would have implications on the control strategy for the column, which would ripple through the control strategy for the rest of the plant. This would lead to control schemes that would never be considered if one looked only at the unit operations in isolation. 

This book deals with control strategies for integrated plants. In most cases the plant consists of a separate reaction section followed by a refining section with recycles between the two. Optimal designs usually call for tight integration of the unit operations, as we mentioned in Chaps. 2 and 5. What if we could take the ultimate step in integration and combine the reaction and separation sections "We would then have reactive distillation. 

Systems that have the most potential for reactive distillation are those where the reaction is reversible, heat of reaction is not excessively large, and the products have the correct volatilities in relation to the reactants. Those systems reach chemical equilibrium (i.e., reaction stops) unless the reactants are in large excess or the products are continuously removed. An example system has been reported in the literature by Eastman Chemical (Agreda et al., 1990) for the production of methyl acetate from methanol and acetic acid. The discussion about process operation and the control strategy shown in the paper certainlv adhere to the plantwide control principles we have outlined in this book. 

There are many other aspects of distillation column control in a plantwide context. One of the earliest studies of these issues is the work of Downs (1992). According to Downs, the control strategy for each unit operation must be developed within the framework of the overall component inventory control structure. 7 He presents several... 

The availability of detailed models and solution methods has enabled many new studies of complex, mixtures, configurations, and operating and control strategies for batch distillation. 

Similarly to our approach, Luyben and co-workers [4, 5] proposed to fix the reactor-inlet flow rate of acetic acid and to use the fresh feed to control the inventory in the bottom of the acetic-acid distillation column. The two control strategies are equivalent... 

Neural and fuzzy applications have been successfully applied to the chemical engineering processes [1], and several control strategies have been reported in literature for the distillation plant modeling and control tasks [2]. Recent years have seen a rapidly growing number of neurofuzzy control applications [3]. Beside this, several software products are currently available to help with neurofuzzy problems. 

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