Control of Highly Interconnected Reactive Distillation Processes

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Control of highly interconnected reactive distillation processes: purification of raw lactic acid by esterification and hydrolysis Chien-Yuan Su, Cheng-Ching Yu, I-Lung Chien, and Jeffrey Daniel Ward Ind. Eng. Chem. Res., Just Accepted Manuscript • DOI: 10.1021/ie5039133 • Publication Date (Web): 12 Jun 2015 Downloaded from http://pubs.acs.org on June 21, 2015

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Industrial & Engineering Chemistry Research

Control of highly interconnected reactive distillation processes: purification of raw lactic acid by esterification and hydrolysis Chien-Yuan Su, Cheng-Ching Yu, I-Lung Chien and Jeffrey D. Ward* Department of Chemical Engineering National Taiwan University Taipei 10617, Taiwan

Abstract Plantwide control of processes to purify lactic acid by esterification and subsequent hydrolysis are investigated. Two processes are considered and compared: one using methanol and the other using butanol. The alcohol liberated in the hydrolysis column is recycled to the esterification column, and the water liberated in the esterification column can be re-used in the hydrolysis column, resulting in highly-interconnected process flowsheets. For both processes, designs with one recycle stream (alcohol only) and two recycle streams (alcohol and water) are tested, and for each alcohol and each configuration, both temperature and composition control are tested for all columns (reactive and non-reactive). The results show that processes with only a single recycle stream are somewhat easier to control. For the butanol process, a temperature control structure with only a single composition controller is found to be adequate, while additional composition measurements with constraints on

*

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controller outputs are required for good control of the methanol process. For both processes, responses are more symmetric when temperature control structures are used. Keywords: Lactic acid; process control; temperature control; composition control.

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1

Introduction Lactic acid (C3H6O3.) is naturally occurring low-molecular weight carboxylic acid. Its

polymer, poly-lactic acid (PLA), has found application as a biodegradable plastic. Lactic acid can be produced either by fermentation or synthetically from petrochemical feedstocks. Purification of crude lactic acid produced by fermentation is challenging because lactic acid has a high normal boiling point and an affinity for water, and it can also oligomerize at moderate temperatures. All of these factors make separation by distillation difficult. Various methods of purification have been investigated; a review is provided by Data and Henry.1 One method that has received attention in the literature2-6 is to react the lactic acid with an alcohol to form a lower-boiling ester which can be separated from heavy impurities. The ester can then be hydrolyzed to recover purified lactic acid. This method can produce a concentrated lactic acid product suitable for use in the production of PLA. Recently, Su et al.7 compared processes to purify lactic acid using different alcohols. The results indicated that among C1–C5 alcohols (methanol to pentanol), methanol and butanol were the most economically attractive. Methanol is inexpensive, forms no azeotrope with water and forms the lightest-boiling ester, while butanol induces a liquid-liquid phase split that can be exploited to reduce separation costs. Processes employing ethanol, propanol and pentanol were found to be more expensive due to the formation of homogeneous azeotropes with water in the case of ethanol and propanol and due to higher energy consumption for the 3



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separation of the less volatile ester in the case of pentanol. Both processes rely on two reactive distillation columns (one for esterification and one for hydrolysis) and both require the recycle of the alcohol liberated in the hydrolysis reaction for re-use in the esterification column. Ideally, water liberated in the preconcentrator column or the esterification column would also be reused in the hydrolysis column to reduce fresh water consumption and the production of wastewater. It has long been recognized that the dynamics and controllability of design alternatives should be investigated in the early stages of process development, especially for highly integrated processes.8,

9

Since both the methanol and butanol processes appear attractive

based on preliminary steady-state design analysis, it is worthwhile to study the dynamics and controllability of both processes. Such a study can reveal whether there are any inherent problems with controllability of either process and whether either alternative has any advantages in terms of dynamic operability or control. That is the purpose of this work. Many methods for controlling processes have been developed, however the most widely used method in industry is decentralized PID control.8 We agree with the point of view of Luyben8, 9 who says that the simplest method of process control that works well is the one that should be used. Therefore we first try to develop a decentralized PID control structure for each design alternative that can meet the process constraints in the face of reasonable disturbances and provide good dynamic performance. If such a decentralized control structure 4


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cannot be identified, then advanced methods are tested in order of increasing complexity until good control is achieved. The method of developing the control structures is a combination of heuristics and numerical analysis similar to that suggested by Luyben8, 10 and Murthy-Konda et al.11 The remainder of this manuscript is organized as follows: In Section 2, the steady-state design of the two processes is reviewed. In Section 3, control structures based on composition measurements are presented and evaluated. In Section 4, control structures based primarily on column temperature measurements are presented and discussed. In Section 5, a control structure employing composition-temperature cascade controllers is presented and discussed. Finally, in Section 6 conclusions are presented.

2. Process description In this section, the processes to purify lactic acid with methanol and butanol are briefly reviewed. Further details, including the kinetic and thermodynamic models used in this work, are provided by Su et al.7 The process dynamics are modeled using Aspen Dynamics 7.2 and the UNIQUAC equation was used to predict the vapor-liquid equilibrium. Both processes produce produce a product that is 88 wt% lactic acid, 12 wt% water. This is the composition in which lactic acid is stored, sold and transported. At a higher composition (with less water) lactic acid may spontaneously polymerize in storage. Constraints (which apply to both processes) are listed in Table 1. 5



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2.1 Methanol process Lactic acid can react reversibly with methanol to produce methyl lactate and water: LA + MeOH ↔ MeLac + Hଶ O The methanol process has four columns, as shown in Figure 1. There are two reactive distillation columns and two non-reactive distillation columns. Raw lactic acid is fed into a preconcentrator column where excess water in the feed is removed. The concentrated lactic acid is fed to the top of the esterification column where it is reacted with methanol fed at the bottom. Methyl lactate and water are collected at the top of the column and heavy impurities are removed at the bottom. The methyl lactate and water are fed to the hydrolysis column, where additional water is supplied and the reverse reaction (hydrolysis) takes place. Purified concentrated lactic acid in water is removed from the bottom of the hydrolysis column, and water and methanol are collected at the top of the column. Finally, in the recovery column, high-purity alcohol is collected and recycled to the esterification column and excess water is removed. To reduce the demand for fresh water and the production of waste water, water from either stream 2 or stream 10 can be fed to the hydrolysis column (stream 7). 2.2 Butanol process Lactic acid can also react reversibly with butanol to produce butyl lactate and water: LA + BuOH ↔ BuLac + Hଶ O The butanol system has five columns including three separation columns and two reactive 6


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distillation columns. Figure 2 shows the optimal flowsheet for the butanol system. The fresh feed enters the preconcentrator and the effluent from the preconcentrator is fed to the esterification column. Because there is a liquid-liquid equilibrium zone, the esterification column has a decanter on top to separate and remove high purity water. This improves the efficiency of the esterification reaction, but it also means that a separate column is required to remove the heavy impurity. (Unlike the methanol process where the impurity is removed from the bottom of the esterification column.) The top product from the esterification column contains mostly water and is fed directly to the hydrolysis column. The bottom product is fed to a heavy impurity removal column. The heavy impurities are removed from the bottom of this column and a stream containing primarily butyl lactate is collected at the top and fed to the hydrolysis column. The hydrolysis column also has a two-liquid-phase decanter at the top. A stripping column is employed to recover high purity butanol, similar to a traditional azeotropic distillation, which makes alcohol recovery portion of the flowsheet simpler and less expensive than that of the methanol process.

3. Composition control structures As a starting point, it was assumed that composition measurements were available at the top and bottom of all columns if necessary. Unless otherwise stated, all controllers were tuned using sequential relay feedback tuning12,

13

and Tyreus-Luyben tuning parameters (‫ܭ‬௖ =

‫ܭ‬௨ /3 and ߬ூ = 2ܲ௨ ). For all composition measurements, an analyzer dead time of five 7



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minutes is assumed. 3.1 Composition control structure designs The composition control structure for the process using methanol with one recycle stream is shown in Figure 3. The reflux ratio was fixed in the preconcentrator, esterification and hydrolysis columns. This allows for a faster dynamic response because these controllers can be tuned more aggressively than temperature or composition controllers. The feed ratios (the ratio of the lower feed rate to the upper feed rate) of the esterification and hydrolysis columns were also fixed. Composition control was employed at the bottom of each column and also at the top of the alcohol recovery column. In total there are 9 level controllers and 4 pressure controller for inventory control and 5 composition controllers for quality control. The control structure for the process with two recycle streams is the same as that for the one-recycle case, except that the aqueous feed to the hydrolysis column is drawn primarily from the aqueous product of the alcohol purification column. A control structure diagram is shown in the supplement in Figure S1. Controlled and manipulated variables for critical loops as well as corresponding constraints are provided in the supplement in Table S1. The control structure for the process with butanol and one recycle stream is shown in Figure 4. Like the methanol process, the reflux ratio in the preconcentrator column and the feed ratio and reflux ratio of the esterification and hydrolysis columns are fixed. The control structure has 12 level controllers and 5 pressure controllers for inventory control and 6 8


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composition controllers for quality control. The control structure for the butanol process with two recycle streams is similar except that the aqueous feed to the hydrolysis column is drawn from the aqueous outlet flow from the decanter of the esterification column. A control structure diagram is shown in the supplement in Figure S2. Controlled and manipulated variables for critical loops as well as corresponding constraints are provided in the supplement in Table S2. 3.2 Composition control dynamic responses Step changes in the feed flow rate (+/− 10%), lactic acid composition (+/− 0.05 weight fraction) and heavy impurity composition (+/− 0.03 weight fraction) were applied to the systems to test the control structure performances. The dynamic responses of the methanol process with one recycle stream and composition control are shown in the supplement in Figures S3–S5. The purity of methanol and water in the alcohol separation column remain close to 99 mol% and the conversion of lactic acid and methyl lactate in the esterification and hydrolysis columns also remain close to 0.99. The product composition remains near the desired value of 88 wt% L1+L2. However, the temperature in the reactive section of the esterification column exceeds the 120 oC temperature constraint associated with the catalyst during the transient time between steady states. Similar results are observed for the process with two recycle streams, as shown in Figures S6–8. The dynamic responses for the butanol process with one recycle stream and composition 9



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control are shown in Figures S9–11. Most of the controlled variables return to a new steady state within 20 hours after disturbance. The product composition remains very close to the desired value of 88wt% L1+L2. The temperatures at the bottom of the esterification and hydrolysis columns remain below 120oC at all times. The stripping column butanol purity remains close to 99 mol% and the conversion of lactic acid in the esterification column also remains close to 0.99. The conversion of butyl lactate takes longer to reach a new steady state value, the value is also close to 0.987. In summary, composition control achieves all of the control objectives listed in Table 1. Similar results were observed for the butanol process with two recycle streams, as shown in Figures S12–14.

4. Column temperature control Although composition control was shown to give satisfactory results, in practice temperature control of distillation columns (both reactive and non-reactive) is preferred because temperature measurements are faster, less expensive and more reliable than composition measurements. Therefore control structures based on column temperature measurements were also developed. The method of Hung et al.14 and Luyben and Yu15 was applied to determine the temperature control structure for each column. Briefly, their procedure is: 1. Select a manipulated variable. Typically, the manipulated inputs are the reboiler duty, reflux ratio and feed ratio. 2. Perform open-loop sensitivity analysis to test the temperature sensitivity of each tray. 10


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Trays that respond in the same direction for both increase and decrease of manipulated variable cannot be used as controlled variable. Use the non-square relative gain (NRG)16 to select the temperature control trays. The largest values of the row sums of the NRG indicate good candidate temperature control trays. 3. Use the relative gain array (RGA)17 for variable pairing once the inputs and outputs are determined. 4. Use sequential relay feedback tests12, 13 to find the ultimate gain (Ku) and the ultimate period (Pu). 5. Use a modified version of the Tyreus-Luyben18 tuning relations to determine the parameters for the PI controllers: Kc=Ku/3 and τ I=2Pu. 4.1 Methanol process sensitivity analysis, NRG/RGA results and control structures The methanol process has two reactive distillation columns and two nonreactive distillation columns. The feed ratio and the reboiler duty were selected as the two manipulated variables for the reactive distillation columns, and the reflux ratio and the reboiler duty were selected for the non-reactive distillation columns. Adjustments of ±0.1% in manipulated variables were made to find the open-loop sensitivity in the four columns. In order to find the steady-state gains of tray temperatures in the linear region, very small step changes in the manipulated variables were made. 11



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Figures S15–S18 in the supplement show the open-loop sensitivity results for all columns in the methanol process. As expected for all columns, an increase in heat input (QR) leads to a temperature increase in the columns. For the preconcentrator column, temperature control only at the bottom of the column was found to be sufficient, therefore the reflux rate is maintained constant. For the alcohol recovery column, increasing the reflux flow rate decreases the column temperature. The esterification and hydrolysis columns have two additional manipulated variables besides for the reboiler duty: the reflux rate and the feed ratio. As expected, the temperature of both columns decreases when the reflux ratio increases. The sensitivity diagrams show that all columns have symmetric responses and the steady state gain is between 0~8000 (delta T/0.1% oC). Next the NRG can be used to calculate the row sum and identify good candidate trays for temperature control: ઩ே = ࡷ ⊗ (ࡷା )் Here, ઩ே stands for the NRG; ⊗ denotes element-by-element multiplication; and the superscripts T and + correspond to transpose and pseudo-inverse, respectively. Trays with a large row sum are good candidates for temperature control. From the results, in the preconcentrator column, the reflux ratio and reboiler duty should be manipulated to control T2 and T3; in the esterification column the feed ratio and reboiler duty should be manipulated to control T20 and T21; in the hydrolysis column the feed ratio and reboiler duty should be manipulated to control T2 and T89, and in the recovery column the 12


(1)

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reflux ratio and reboiler duty should be manipulated to control T9 and tray T19. Table 2 shows the RGA result for four columns and the suggested pairings based on the RGA results. After control pairing is done, relay feedback tests are used to find the ultimate gain (Ku) and the ultimate period (Pu) and Tyreus-Luyben PI tuning rules are used to determine the tuning parameters. The identification-tuning step is carried out sequentially to find the controller settings for the PI controllers. Note that for the preconcentrator column only the reboiler duty was manipulated to control a tray temperature (tray 3) and the reflux ratio was maintained constant. Table 2 summarizes the settings for all PI controllers in the system. The column temperature control structure for the methanol process with one recycle stream is shown in Figure 5. It includes 9 level controllers and 4 pressure controllers for inventory control and 7 temperature controllers for quality control. Dynamic simulations showed that in order to maintain good control of the process, it was necessary to include a single composition controller to control the product quality (the composition of lactic acid in the bottom of the hydrolysis column). The composition controller is cascaded onto the temperature controller that manipulates the reboiler duty to control the temperature at the bottom of the column. Reflux ratio is also fixed in both reactive distillation columns. The control structure for the methanol process with column temperature control and two recycle streams is similar and is shown in Figure S19 in the supplement. Controlled and manipulated 13



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variables for critical loops as well as corresponding constraints are provided in the supplement in Table S3. 4.2 Methanol temperature control dynamic responses The dynamic responses of the methanol process with column temperature control and one recycle stream are shown in Figures S20–S22 in the supplement. Most variables return to a new steady state within 60 hours. The recycle column methanol purity and water purity are close to 99 mol% and the conversion of lactic acid and methyl lactate is also close to 0.99. The product composition remains very near to 88 wt% of L1+L2 and the tray temperatures remain below 120 oC in both reactive zones in the reactive distillation columns. When the mass fraction of impurity in the process feed is decreased (Figure S22), an abrupt change in the dynamic response is observed after about 15 hours. The reason for this change is that the valve on the methanol recycle stream has become saturated (fully open). The feed ratio of methanol to lactic acid is manipulated to control a tray temperature in the esterification column. When the amount of impurity in the feed is significantly reduced, the temperature in the bottom of the esterification column (where the heavy impurity is removed) will tend to rise because the composition of heavy impurity will increase. (A smaller amount of impurity in the feed makes the separation easier, with the result that the concentration of impurity in the bottom increases.) The controller responds by increasing the flow rate of methanol. However this action is unnecessary in this case because the decrease in the amount 14


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of impurity is a favorable situation. Although the composition of methyl lactate in the impurity stream increases, the rate of loss of methyl lactate in the impurity stream decreases because the impurity stream flow rate also decreases. Furthermore, a further increase in the methanol flow rate to the column consumes energy throughout the process as the excess methanol circulates through columns 2-4. Therefore a constraint on the methanol feed flow rate is imposed to prevent an unnecessary excess flow rate. The dynamic responses for the process with methanol and column temperature control with two recycle streams are shown in Figures S23–S25. Results are similar to the results for the process with one recycle stream. The same abrupt change in the dynamic response for the case of decreasing the impurity feed composition is observed for the same reason. 4.3 Butanol process sensitivity analysis, NRG/RGA results and control structures The same procedure applied to design the column temperature control structure for the methanol process was also applied to the butanol process. The butanol process has two reactive distillation columns and three non-reactive distillation columns. For the esterification and hydrolysis columns, feed ratio and reboiler duty are considered as candidate manipulated variables. For the preconcentrator column and the impurity removal column, reflux ratio and reboiler duty are chosen as manipulated variables. For the alcohol recovery column, single end temperature control is employed (only the reboiler duty is manipulated) because the top product from the alcohol recovery column is fed back to the decanter. Step changes of ±0.1% 15



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in the manipulated variables were applied and the open-loop sensitivity of the tray temperatures in the columns was determined. Figures S26–29 show the open-loop sensitivity results in all columns except the alcohol recovery column in the butanol system. For all columns, an increase in heat input (QR) leads to a temperature increase in the columns and vice versa. In the preconcentrator column and the impurity removal column, increasing the reflux ratio causes a decrease in column temperatures. In the esterification column, increasing the feed ratio decreases the column temperature, while in the hydrolysis column it increases the column temperature. Table 3 shows the results of the column temperature control structure design for all columns in the butanol process. Figure 6 shows the resulting control structure for the butanol process with one recycle stream and column temperature control. The control structure for the process with two recycle streams is similar and is shown in Figure S30 in the supplement. Controlled and manipulated variables for critical loops as well as corresponding constraints are provided in the supplement in Table S4. Both control structures have 5 pressure controllers for inventory control and 8 temperature controllers for quality control. The process with one recycle stream has 12 level controllers and the process with two recycle streams has 13 level controllers. Like the methanol process, one composition controller is cascaded onto the temperature controller that manipulates the reboiler duty in the hydrolysis column. This controller maintains the lactic acid stream 16


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product specification. 4.4 Butanol process with column temperature control dynamic responses The same disturbances applied previously were also applied to the butanol process with column temperature control. The dynamic results for the process with one recycle stream are shown in Figures S31–S33 in the supplement. Most process variables reach a new steady state within 10 hours. The recycle column butanol purity is close to 99 mol% and the conversion of lactic acid and methyl lactate is also close to 0.99. The product specification of lactic acid can achieve 88 wt% of L1+L2 and the tray temperatures remain below 120 oC in both reactive zones in the reactive distillation columns. All dynamic results are symmetric except for the bottom butyl lactate composition in the impurity removal column when the impurity composition is changed. As discussed previously for the methanol process, when the composition of impurity decreases, the control structure has difficulty maintaining the bottom temperature in the impurity removal column when the amount of impurity is decreased. However this is not a problem because the rate of loss of butyl lactate remains small. The dynamic responses for the butanol process with column temperature control and two recycle streams are shown in Figures S34–36 in the supplement. In general the results are similar to those of the same process with one recycle stream, however the process takes longer to achieve steady state. This reflects the fact that when water is recycled in the process, 17



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small amounts of impurities are recycled as well. 5. Composition-temperature cascade control structure So far control structures have been developed based on either column temperature measurements or product composition measurements. Although both methods work well, they both suffer from certain drawbacks. For the methanol process under composition control, the temperature in the esterification column may exceed the constraint during the transient period between steady states. For both the methanol and butanol processes under temperature control, the controller manipulating the reboiler duty in the column where the heavy impurity is removed struggles to maintain the temperature when the mass fraction of impurity in the feed is decreased. To address these shortcomings, an additional control structure is proposed and tested for the

methanol

process

with

one

recycle

stream.

The

control

structure

uses

composition-temperature cascade structures, in which the setpoint for the column temperature controllers is determined by composition controllers. In this way a limit can be set on the temperature setpoint in the esterification column to avoid exceeding the constraint in the transient between steady states. Furthermore, the controller controlling the impurity composition can adjust the setpoint for the temperature controller in the case of a decrease in the impurity feed mass fraction, thereby avoiding the problem where the temperature controller struggles to maintain the column temperature. Thus, by working together, the 18


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temperature and composition controllers may give a better result than either method could achieve on its own. The proposed control structure with cascade controllers is shown in Figure 7. The reflux ratio in the preconcentrator, esterification and hydrolysis columns are fixed, as are the feed ratio of the esterification and hydrolysis columns. The trays for temperature control are the same as those identified for the temperature control structure. There are in total 9 level controllers and 4 pressure controllers for inventory control; and 4 composition-temperature cascade controllers for quality control. The same disturbances considered for the other control structures were applied, and the results are shown in Figures S37–S39. The product specification of lactic acid achieves 88wt% of L1+L2. The reactive tray temperatures remain below 120 oC in both reactive distillation columns. A constraint on the temperature controller setpoint of 120 oC is employed in the esterification column. When the mass fraction of impurity is decreased (Figure S39) the constraint is reached after about 16 hours. Thereafter, the esterification column temperature remains at 120 oC. At the same time, the composition of methyl lactate in the product impurity stream begins to rise. However, as stated previously, this is not undesirable because the rate of loss of methyl lactate has actually decreased compared to the initial steady state. The composition of methyl lactate in the impurity eventually reaches a new steady-state value. The recycle column methanol purity and water purity remain close to 19



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99 mol% and the conversion of lactic acid and methyl lactate is also close to 0.99 and 0.98. The results show that the cascade control structure is the most effective when faced with different types of disturbances.

6. Conclusion Plantwide control structures have been developed and tested for processes to recover lactic acid by esterification and hydrolysis in reactive distillation columns. A total of four flowsheets are considered, two with methanol and two with butanol. For each alcohol, a process design with one recycle stream (alcohol only) and two recycle streams (alcohol and water) are considered. For each flowsheet, two control structures are designed, one using composition measurements and one relying primarily on column temperature measurements. Finally, one additional control structure employing composition-temperature cascade controllers is designed and tested for the methanol process with one recycle stream. All control structures are tested with disturbances in the feed flow rate, mass fraction of lactic acid in the feed, and mass fraction of impurity in the feed. Table 4 shows the average value of the integral of the absolute value of the error (IAE) for the methanol and butanol processes under both temperature and composition control as well as the proposed cascade control structure for the methanol process. These values were calculated by averaging the IAE for temperature and composition control loops for each structure in response to the three disturbances described previously. The average IAE has 20


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different units for temperature and composition control, so direct comparison between these values is not possible. The results show that the methanol process is somewhat easier to control, and that the proposed cascade control structure improves the overall controllability of the methanol process under temperature control. For the butanol process, a control structure that primarily relies on column temperature measurements with only a single composition measurement (the composition of the product) can provide effective control in the face of many different types of disturbances. The composition control structure is also effective for the butanol process, but may not be preferred due to the difficulty of composition measurements. For the methanol process, the temperature in the reactive section of the esterification column exceeds the temperature constraint in the transient period between steady states when composition control is employed. When temperature control is employed, the valve on the methanol recycle stream saturates as the control structure attempts to maintain column temperature when the feed mass fraction of impurity is decreased. Thus a combined composition-temperature cascade control structure performs the best for this process.

Acknowledgement The authors thank the National Science Council of Taiwan and the Taiwan Ministry of Economic Affairs for supporting this research.

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Supporting Information Available Additional figures and tables are provided as supporting information. This information is available free of charge via the Internet at http://pubs.acs.org/.

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References 1.

Datta, R.; Henry, M., Lactic acid: recent advances in products, processes and technologies - a review. Journal of Chemical Technology and Biotechnology 2006, 81, 1119-1129.

2.

Cockrem, M. C. M.; Johnson, P. D. Recovery of lactate esters and lactic acid from fermentation broth. 5,210,296, 1993.

3.

Kamble, S. P.; Barve, P. P.; Joshi, J. B.; Rahman, I.; Kulkarni, B. D., Purification of Lactic Acid via Esterification of Lactic Acid Using a Packed Column, Followed by Hydrolysis of Methyl Lactate Using Three Continuously Stirred Tank Reactors (CSTRs) in Series: A Continuous Pilot Plant Study. Industrial & Engineering Chemistry Research 2012, 51, 1506-1514.

4.

Kumar, R.; Mahajani, S. M., Esterification of lactic acid with n-butanol by reactive distillation. Industrial & Engineering Chemistry Research 2007, 46, 6873-6882.

5.

Kumar, R.; Nanavati, H.; Noronha, S. B.; Mahajani, S. M., A continuous process for the recovery of lactic acid by reactive distillation. Journal of Chemical Technology and Biotechnology 2006, 81, 1767-1777.

6.

Liu, M.; Jiang, S. T.; Pan, L. J.; Zheng, Z.; Luo, S. Z., Design and control of reactive distillation for hydrolysis of methyl lactate. Chemical Engineering Research & Design 2011, 89, 2199-2206. 23



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7.

Su, C. Y.; Yu, C. C.; Chien, I. L.; Ward, J. D., Plant-Wide Economic Comparison of Lactic Acid Recovery Processes by Reactive Distillation with Different Alcohols. Industrial & Engineering Chemistry Research 2013, 52, 11070-11083.

8. Luyben, W. L.; Tyréus, B. r. D.; Luyben, M. L., Plantwide process control. McGraw-Hill: New York, 1998; p xvi, 395 p. 9.

Luyben, W. L., Plantwide dynamic simulators in chemical processing and control. Marcel Dekker: New York, 2002; p ix, 429 p.

10. Luyben, M. L.; Tyreus, B. D.; Luyben, W. L., Plantwide control design procedure. Aiche Journal 1997, 43, 3161-3174. 11. Konda, N. V. S. N. M.; Rangaiah, G. P.; Krishnaswamy, P. R., Plantwide control of industrial processes: An integrated framework of simulation and heuristics. Industrial & Engineering Chemistry Research 2005, 44, 8300-8313. 12. Yu, C.-C., Autotuning of PID controllers : a relay feedback approach. 2nd ed.; Springer: London, 2006; p xiii, 261 p. 13. Shen, S. H.; Yu, C. C., Use of Relay-Feedback Test for Automatic Tuning of Multivariable Systems. Aiche Journal 1994, 40, 627-646. 14. Hung, S. B.; Lee, M. J.; Tang, Y. T.; Chen, Y. W.; Lai, I. K.; Hung, W. J.; Huang, H. P.; Yu, C. C., Control of different reactive distillation configurations. Aiche Journal 2006, 52, 1423-1440. 24


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15. Luyben, W. L.; Yu, C.-C., Reactive distillation design and control. Wiley : AIChE: Hoboken, N.J., 2008; p xxi, 574 p. 16. Chang, J. W.; Yu, C. C., The Relative Gain for Nonsquare Multivariable Systems. Chemical Engineering Science 1990, 45, 1309-1323. 17. Bristol, E. H., On a New Measure of Interaction for Multivariable Process Control. Ieee Transactions on Automatic Control 1966, Ac11, 133-134. 18. Luyben, M. L.; Luyben, W. L., Essentials of process control. McGraw-Hill: New York, 1997; p xx, 584 p.

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Tables Table 1 Process constraints. Column

Constraints

Preconcentrator

T < 80oC

Esterification

Trxn < 120oC Trxn < 120oC

Hydrolysis

L1+L2=88 wt%

Table 2 Controlled variables, manipulated variables and relative gain array for four columns in methanol system Column

Controlled

Manipulated

variables

variables

T2

RGA

RR

Pre.

Duty Λ

 0.477 =  0.523

T3

QR

T20

FR

Duty

T21

QR

 − 0.472 =  1.472

T2

FR

Duty

T89

QR

 0.049 =  0.951

T9

RR

Duty

QR

 − 0.463 =  1.463

Est.

QR-T3: Kc=30.78

τI=3.96(min)

FR 1.472  T20 − 0.472  T21

Kc=9.512

τI=249.48(min)

QR-T21: τI=14.52(min)

QR-T89: FR 0.951  T2 0.049  T89

Kc=39.15

τI=13.2(min)

FR-T2: Kc=4.07

τI=26.4(min)

RR-T9: Λ

T19

0.523  T2 0.477  T3

Kc=2.305

Λ

Rec.

RR

FR-T20: Λ

Hyd.

Tuning parameter

RR 1.463  T9 − 0.463  T19

Kc=61.135 τI=26.4(min) QR-T19: Kc=7.087

26


τI=13.2(min)

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Table 3 Controlled variables, manipulated variables and relative gain array for four columns in butanol system Column Pre.

Controlled

Manipulated

variables

variables

T2

RR

T3

QR

T17

FR

Duty

T4

QR

 0.995 =  0.005

T9

FR

Duty

T10

QR

 0.1895 =  0.8104

T26

FR

Duty

T53

QR

 0.0012 =  0.9988

T4

QR

Est.

τI=13.2(min)

Kc=1.935

FR-T17: FR 0.005  T4 0.995  T17

Kc=2.414 τI=10.56(min) QR-T4: τI=13.2(min)

Kc=29.935

QR-T9: Λ

Hyd.

Tuning parameter RR-T3:

Λ

Est-sep

Recov.

RGA

RR 0.8104  T9 0.1895  T10

τI=18.48(min)

Kc=1.482

RR-T10: τI=18.48(min)

Kc=4.344

FR-T26: Λ

FR 0.9988  T26 0.0012  T53

Kc=115.1204

τI=18.48(min)

QR-T53: Kc=20 τI=0.2(min) QR-T4: Kc=0.72 τI=21.12(min)

Table 4: Integral of the absolute value of the error (IAE) for different control structures System Methanol Butanol Methanol

Control structure

IAE

Temperature Composition Temperature Composition Cascade

0.317802 °C·hr 0.0179 wt frac·hr 2.4453 °C·hr 0.03485 wt frac·hr 0.05088 wt frac·hr

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Figures

Figure 1: Flowsheet for methanol process.

Figure 2: Flowsheet for butanol process.

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Figure 3: Composition control structure for process using methanol with one recycle stream.

Figure 4: Composition control structure for process using butanol with one recycle stream

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Figure 5 Temperature control structure for process using methanol with one recycle stream

Figure 6 Temperature control structure for process using butanol with one recycle stream

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Figure 7 Composition-temperature cascade control structure for process using methanol with one recycle stream

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Page 32 of 32

For Table of Contents Only

TC

0.00992 PC LC

0.00868

FT

NFLAC=2

FT

FC

0.00806

X

FR

0

RR X

+20% Flow rate -20% Flow rate

0.00930

LAC

5

10

15

20

TC

NRXN=19 FC

T20 T21

FT

MeOH

0.0110

TC

NMeOH=20

LC

0.0099 +5% LAC Comp. -5% LAC Comp.

Steam

0.0088 0.0077 0

5

10

15

Time (Hours)

32


20

Control of Highly Interconnected Reactive Distillation Processes

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