Base Case Control Structure

Figure 17.20 RGA number, a) control alternatives in the base-case b) structure I1-Q2 and I3-D4 in all alternatives...

Figure 11.13 shows the control structure for the heat-integrated extractive system. The three block arrows point to the changes that have been made from the base-case control stmcture. 

The ammonium catalyst can also influence the reaction path and higher yields of the desired product may result, as the side reactions are eliminated. In some cases, the structure of the quaternary ammonium cation may control the product ratio with potentially tautomeric systems as, for example, with the alkylation of 2-naph-thol under basic conditions. The use of tetramethylammonium bromide leads to predominant C-alkylation at the 1-position, as a result of the strong ion-pair binding of the hard quaternary ammonium cation with the hard oxy anion, whereas with the more bulky tetra-n-butylammonium bromide O-alkylation occurs, as the binding between the cation and the oxygen centre is weaker [11], Similar effects have been observed in the alkylation of methylene ketones [e.g. 12, 13]. The stereochemistry of the Darzen s reaction and of the base-initiated formation of cyclopropanes under two-phase conditions is influenced by the presence or absence of quaternary ammonium salts [e.g. 14], whereas chiral quaternary ammonium salts are capable of influencing the enantioselectivity of several nucleophilic reactions (Chapter 12). 

So the multiloop SISO diagonal controller remains an important structure. It is the base case against which the other structures should be compared. The procedure discussed in this chapter was developed to provide a workable, stable, simple SISO system with only a modest amount of engineering effort. The resulting diagonal controller can then serve as a realistic benchmark, against which the more complex multivariable controller structures can be compared. 

Because of the difficulties in family-based design, an association study with a case-control design is more and more commonly used by investigators. Because of the concern of confounding caused by population structure and recent admixture, appropriate adjustment of stratification should be used in association studies. A number of approaches have been developed for this purpose. 

Figure 3.39 gives the response of the system to a step 20% increase in the flowrate of the reactor effluent. The control structure provides good base-level regulatory control. The maximum deviation in reactor temperature is 0.6 K. Three cases are shown. In the first, the reflux flowrate is held constant. In the second, the reflux is ratioed to the feed. There is little difference in the responses of the reactor. But with a fixed reflux flowrate, the impurity of C in the distillate xDC increases from 0.0164 to about 0.025 mole fraction C. With the reflux-to-feed ratio, the impurity remains about the same. The change in the vapor boilup is larger with the reflux-to-feed structure. 

The parameters of the pore structure, such as surface area, pore volume, and mean pore diameter, can generally be used for a formal description of the porous systems, irrespective of their chemical composition and their origin, and for a more detailed study of the pore formation mechanism, the geometric aspects of pore structure are important. This picture, however, oversimplifies the situation because it provides a pore uniformity that is far from reality. Thorough attempts have been made to achieve the mathematical description of porous matter. Researchers discussed the cause of porosity in various materials and concluded that there are two main types of material based on pore structure that can be classified as corpuscular and spongy systems. In the case of the silica matrices obtained with TEOS and other precursors, the porous structure seems to be of the corpuscular type, in which the pores consist of the interstices between discrete particles of the solid material. In such a system, the pore structure depends on the pores mutual arrangements, and the dimensions of the pores are controlled by the size of the interparticle volumes (1). 

However, we see in this strategy that there is no flow controller anywhere in the recycle loop. The flows around the loop are set based upon level control in the reactor and reflux drum. Given what we said above, we expect to find that this control structure exhibits the snowball effect. By writing the various overall steady-state mass and component balances around the whole process and around the reactor and column. wre can calculate the flow of the recycle stream, at steady state, for any given fresh reactant feed flow and composition. The parameter values used in this specific numerical case are in Table 2.1. 

With the control structure in Fig. 2.6 and the base-case fresh feed flow and composition, the recycle flowrate is normally 260.5 moles/h. However, the recycle flow must decrease to 205 moles/h when the fresh feed composition is 0.80 mole fraction A. It must increase to 330 moles/h when the fresh feed compositon changes to pure A. Thus a 25 percent change in the disturbance (fresh feed composition) results in a 60 percent change in recycle flow. With this same control structure and the base-case fresh reactant feed composition, the recycle flow drops to 187 moles/h if the fresh feed flow changes to 215 moles/h. It... 

For example, let us consider a simple distillation column in which we have specifications on both the distillate and bottoms products (v-ahK and x b lk We go through the design procedure to establish the number of trays and the reflux ratio required to make the separation for a given feed composition. This gives us a base case from which to start. Then we establish what disturbances will affect the system and over what ranges they will vary. The most common disturbance, and the one that most affects the column, is a change in feed composition. Next we propose a partial control structure. By partial we mean we must decide what variables will be held constant. We do not have to decide what manipulated variable is paired with what controlled variable. We must fix as many variables as there are degrees of freedom in the system of equations. 

In the next two sections, vre select two different control objectives and develop two different control structures, In the first case, we assume that the flowrate of the product stream B leaving the base of the stripper is set by a downstream customer. Hence it is flow-controlled, and the setpoint of the flow controller is a load disturbance to the process. In the second case, we assume that the fresh feed stream is set by an upstream process. So it is flow-controlled, and the setpoint of the flow controller is a load disturbance to the process. These two cases demonstrate that different control objectives produce different control strategies. 

Typical simulation results are shown in Fig. 8.10. At time equals zero, the fresh feed flowrate FoC is reduced by 25 percent from its base-case value. The process responds to this change by gradually cutting back on the other feed streams and the product leaving the unit. The new steady-state conditions are attained in a little over 1 hour. The control structure also successfully handled the other disturbances. 

Figure 10.2 gives the base-case plantwide control structure developed. Total toluene flowrate to the reaction section is flow-controlled. We will make step changes in this flow controller setpoint. Reactor inlet temperature is controlled by the firing rate in the furnace. No heat-exchanger bypass is shown in Fig. 10.2, but we will look at the effect of bypassing the FEHE. Control structure CS2 discussed in Chap. 5 adds a temperature control loop that controls furnace inlet temperature by manipulating the bypass flowrate around the FEHE. See Fig. 5.25. 

New approaches based on the introduction of reactive species into reaction mixtures that tend to cap the growing chains reversibly allow, in many cases, production of well-defined polymers and copolymers with narrow polydispersi-ties. Up to few years ago, such a possibility was unobtainable by a classical free radical process. The proposed principle of control of macroradical reactivity is very interesting conceptually, and represents a very powerful tool to prepare block copolymers with well-controlled structures. However, it is clear that the true living character as demonstrated by some anionic polymerizations is still not obtained and much more work needs to be done to understand and control this new process better. 

The nominal case was taken as a base flow of 400 m /h with no disturbances and no measurement bias. As the disturbances were infrequent, the economic objective for a given control structure was taken to be minimize the excess reagent used at steady state compared to the reagent required with ideal delay-... 

The present case study will show how to solve quantitatively this problem. It will be demonstrated that in the case of large complex plants the inventory of the main components and of impurities cannot be managed separately, because they are coupled through recycles. The interactions can hinder or help the solution of the problem, depending on the competition between positive and negative feedback effects. The implementation of a control structure based on the viewpoint of stand-alone units can lead to conflicts. Hence, a systemic approach based on a quantitative evaluation of the recycle effects is needed (Dimian et al., 2000,2001). 

Thus, the effect of interactions on the control of I3 depends both on the recycle structure and the manipulated variable. Distillate rate D2 gives more interactions compared with the case where the manipulated variable belongs only to S4 (either D4 or Q4). The use of manipulated variables from different units should not be a surprise when these are, dynamically speaking, close enough, as it is the case with S2 and S4. In the base-case and alternative B the effect of the S4 variables on I3 is enhanced by closing the other loops, while in alternatives A and C this effect is hindered. 

The steady-state analysis indicated good sensitivity of the controlled variables to inputs and the possibility to reject disturbances with a diagonal multi-SISO control structures, as for example Q2-Ii, SS2-I2, D2-I3 (see also Table 4). Although there are some differences in the open loop behaviour of flowsheet alternatives as compared to the base-case, these do not justify a net preference. On the other hand, the steady state RGA analysis predicted that a control structure using D2 to control I3 should be more affected by interactions as by manipulating D4 or Q4, but the differences cannot be evaluated only by the inspection of numerical values. Because a steady-state analysis cannot predict how the real disturbances would be handled by the control system, a deeper controllability analysis is necessary in the frequency domain. The battery of indices has been tried in each case, as described by Groenendijk et al.(2000). Here we give only representative results. 

Figure 17.20a shows the evaluation of three control structures in the base-case (1) Q2-Ii, SS2-I2, D2-I3, (2) Q2-Ii, SS2-I2, D4-I3, and (3) Q2-I1, SS2-I2, Q4-I3. All show quasi-constant low values at lower frequencies, up to 0.5 rad/h, in agreement with the steady-state analysis. Rapidly increased RGA-number at higher frequencies indicates a... 

If the loop SS2-I2 is removed, the situation improves considerably. Indeed, the steady-state analysis suggested that best pairing is Q2-Ii and D4-I3. Figure 17.20b presents RGA number for the base-case and alternatives with these combinations, when the control becomes a simple 2x2 structure. In the first place, the plot indicates that base-case and alternative B are practically unaffected by interactions at low frequencies. They behave much better compared to alternatives A and C. The mentioned pairing is feasible for the base-case and the flowsheets A and C up to 10 rad/h, while in alternative B the upper bound is somewhat lower. This frequency range is realistic from plantwide point of view. Hence, the above control structures seem to have good properties. This fact has been verified by closed loop simulation. 

When a large change is made in Zqb,b (to 0.90), the new steady-state values of the manipulated variables were only slightly different from the base-case values. The makeup flow rates of fresh feed change Fqa increases 10 percent and Fqb decreases 10 percent. Production rates of D2 and B3 stay the same, as do other flow rates and compositions throughout the process. Thus, the steady-state sensitivity analysis suggests that this structure should handle disturbances easily. Dynamic simulations confirm that this control structure works quite well. 

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