USE OF A DIGITAL AUTOMATION SYSTEM FOR

PROCESS CONTROL OF A SIMULATED PLANT

By

Mike Ivanusic

(Student #: 60024981)

An undergraduate thesis

Submitted to

Dr. Dusko Posarac

Department of Chemical and Biological Engineering

The University of British Columbia

April 9, 2003

TABLE OF CONTENTSACKNOWLEDGEMENTNOMENCLATUREABSTRACTLIST OF TABLES AND FIGURES IN THE APPENDIXINTRODUCTIONSURVEY OF LITERATURE

A) DeltaV/HYSYS integrationB) Tubular Reactor with Gas Recycle ProcessC) HDA process description

EXPERIMENTAL DETAILSPROCEDURESRESULTS AND DISCUSSIONCONCLUSIONRECOMMENDATIONS FOR FURTHER STUDYLITERATURE CITEDAPPENDIXGRAPHICAL INTERFACE (added Feb 2004)

ACKNOWLEDGEMENT

I wish to thank Dr. Dusko Posarac for suggesting the undertaking of this thesis. His continued enthusiasm for the project, along with his guidance, has been excellent.

I wish to thank Norpac Controls, specifically Don Umbach, for his continued support and interest in the project, and making himself available for my questions. Also, Alden Hagerty of Norpac for his assistance during the graphical interface implementation.

I wish to thank Guan Tien Tan, the Teaching Assistant for CHBE 474, who helped me get a start on the HYSYS/DeltaV OPC integration process.

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NOMENCLATURE

HYSYS: Trade name for a software simulation programDeltaV (dV): Trade name for a digital automation software programHDA: HydrodealkylationOPC: Object link embedding for Process ControlFEHE: Feed effluent heat exchangerXmtr: TransmitterPFD: Process flow diagramLC: Level controllerFC: Flow controllerPID: Proportional Integral DerivativeFF: Feedforward (control)MPC: Model Predictive ControlPCR: Pressure controller recorderRCY: RecycleKc: Gain symbolI: Integral symbolP-only: Proportional only, also known as “Gain”Integral: Area under a curve of defined limits, also known as “Reset”Derivative: slope of the line of interest, also known as “Rate”PFR: Plug flow reactor

ABSTRACT

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Configuration of a simulated chemical plant was performed in the process simulator software package, HYSYS, which has this main feature: the entire process, or even the smallest stream or vessel can be configured in the HYSYS environment. HYSYS is a powerful software simulator package which features: modelling of unit operations, user driven input parameters, chemical reaction capabilities, and static and dynamic modes of operation.

The modelling of the HDA (hydrodealkylation of toluene) process was performed in HYSYS. HYSYS has two main modes of operation: the static mode, where the steady state values are calculated, and the dynamic mode, where the process is modelled similar to a real plant. In the dynamic mode, controllers are added to the process, in a effort to stabilize the actual operations of the plant.

The DeltaV digital process control automation software program’s main advantage is that the software was designed specifically to perform Process Control in the industrial environment. The DeltaV is a large software program featuring: operator interface windows, control strategy building blocks, input and output configurations, alarms and events features, and a host of other advanced control features. Through its many features, solid dynamic control of the HYSYS simulated plant was achieved.

OPC (object link embedding for process control) allows for communication between two software packages. The DeltaV digital automation system has the capabilities of offering advanced control and also has the facility of using the OPC link. The OPC link was utilized in allowing real-time communications between HYSYS and DeltaV. Thus, a line of bi-directional communications was set up between the two software packages. Every controller that was initially in the HDA HYSYS model was rebuilt in the DeltaV digital automation environment. As each controller was being built, the control parameters were modified to produce the optimum control within the plant by performing many different tests and then updating and resetting the control parameters.

The results of this thesis show that the integration of the two software packages offer a large flexibility for several purposes: testing of hypothetical transients, optimization possibilities, operator training, and optimal configuration of a control strategy in the DeltaV before the plant is ever in operation.

LIST OF TABLES AND FIGURES IN THE APPENDIX

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Table1. Table of controllers in the HDA design.Table2. Results of controller optimizationTable3. Product stream compositions at different furnace temperatures Appendix (all listed as figures):

HDA1. Static results, workbook copy, in english unitsdV1. DeltaV ExplorerdV2. DeltaV Control StudiodV3. HYSYS/DeltaV OPC DCS interface windowPCR1. PCR PID DeltaV control upon start-upCC1. Initial fuzzy logic implementationCC2. Changes in fuzzy logic parametersCC3. Continued testing of fuzzy logicCC4. Fuzzy logic begins to return decent controlCC5. Fuzzy logic returns optimal controlTCQ1. TCQ testingTCQ2. Completed testing on the TCQ loopTCQ3. dV Operator interface windowTCQ4. Lag implementation in TCQTCR1. Initial PID attempts at controlTCR2. Initial trial runs of fuzzy logicTCR3. Optimal fuzzy logic control achievedTCR4. Control studio configuration of TCRCC_TCR1. Process response due to interactionCC_TCR2. Response of CC loop due to furnace temperature changesTCQ_large. Large view of dV operate windowAppendix addition: Fuzzy logic: How does it work?

Graphical interface windows (latest additions):HDA_Aug3: Main operator window with pushbuttons leading to main

areasV1_V2_M1: Input to process (input button leading to raw materials and

recycle)FEHE_Fur_PFR: Reaction area-product formationV11_M2: Cooling areaComp_T2_V4: Purge/recycleCond_Sep_T1: Product output

INTRODUCTION

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The distributed control system exists in industrial control situations-these systems are based on analog communications-signals that fluctuate. The digital automation system is based on digital communications-sent and received signals are delivered on a digital bus (encoding of information into 1’s and 0’s).

The advantage of this encoding is the bi-directional communication capabilities-field devices are in contact with the main control system in real time, whereas in analog communications the signals are either only sent or received (uni-directional). A digital automation system now exists known as the DeltaV.

Simulation of a chemical process design (plant), may be done in a process simulator software package, such as ASPEN, HYSYS, CHEMCAD, and PRO/II. HYSYS also has the advantage of adding controllers to the design to simulate dynamic control. The development of the OPC (OLE, object linking embedding for process control), allows communications between the DeltaV digital automation system and the HYSYS simulation environment. Previously, such a communication would not have been possible because of the analog signals associated with the distributed process control system. With the advent of OPC communications, the DeltaV environment can now communicate with the HYSYS environment.

Any chemical plant design may have chemical reactions. Conditions that affect chemical reactions are: temperature, pressure, energy transfer, and concentration. Such a process would understandingly be difficult to control if there were fluctuations within the process. Furthermore, since reactions may not go to completion and/or produce other products, purge and recycle streams are used in the process. Such a plant design would then be a good candidate for HYSYS simulation and the implementation of advanced control features of the DeltaV digital automation system.

The purpose of this thesis was to investigate the advantages of using these two software programs simultaneously; to have the process simulated and running in HYSYS, and then having the control of the process originating in the DeltaV environment.

The chemical design plant simulation is based on the “Hydrodealkylation of Toluene” process. This process produces benzene from toluene and hydrogen; however, a side reaction, producing diphenyl also occurs, which is also a consideration. Only a portion of the full design is modelled in HYSYS-the feed streams, product stream, a (methane) purge stream, a PFR, separator, and other small unit operations.

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BACKGROUND INFORMATION

A. DeltaV/HYSYS integration

The list of features of the DeltaV digital automation system are extensive, and the vast resources of information for this software are readily available. Of interest is the OPC communications link, which enables communications between the DeltaV environment and some other software package. The DeltaV is a powerful and robust software package designed specifically for industrial applications for the control of processes.

HYSYS is a simulation process software, and it also has exhaustive amounts of information available to understand how to use the software. HYSYS simulation aids the designer in configuration, calculations, and testing. Preliminary estimates can be made on the size and scope of the process, unit operations, process line connectivity, and the instrumentation within the process lines.

In the case of a simulated environment, all process instrumentation is assumed to be in good working order-never the case in a real situation since field units are under constant scrutiny for breakdowns. However, for the purposes of simulation, the assumption is that all devices are functioning at peak performance.

B. Tubular Reactor with Gas Recycle Process

The process to be studied is only a portion of a complete design. The complete process is based on the hydrodealkylation, HDA, reactor plant design. Vast amounts of information about this process, along with economic data are available-see references (Douglas 1988). The primary purpose of this section of the plant is to produce benzene from toluene, with the heart of the process centred around the plug flow reactor. For this thesis, the main test unit operations are the reactor, two heat exchangers, a compressor, and a separator drum. Figure 1. shows the configuration that will be entered into the HYSYS environment. Energy recovery is important, so preheating the feed by the hot reactor effluent is in the design. Since per-pass conversion is only moderate and an excess of one of the reactants is required, there is a large gas recycle stream (page 271, Douglas).

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Figure 1. HDA Reactor Section with Gas Recycle

There are two reactions occurring in this process:

1) C7H8 + H2 C6H6 + CH4

-Toluene plus hydrogen goes to benzene and methane. -Exothermic (-18000 Btu/lb-mol)-This is the main reaction with the desired product being benzene.

2) 2C6H6 C12H10 + H2

-Benzene in equilibrium with diphenyl and hydrogen.-Endothermic (3500 Btu/lb-mol)-Side reaction, drawing some benzene into the undesirable compound diphenyl

C. HDA process description

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A gaseous stream of 98 mol% hydrogen and 2 mol% methane, and a liquid toluene stream are both fed to the mixer, M1. These two streams are combined with a large gas recycle stream mixture of hydrogen and methane, Rgas. The mixed stream, cin, is heated by the feed effluent heat exchanger (FEHE), and then the resulting stream, cout, is fed to a fired furnace operating at 1150F and 521 psia.

The heated stream goes to an adiabatic tubular plug flow reactor (PFR) with no catalyst. The reactor feed contains 376 lb-mol/hr of toluene and 2132 lb-mol/hr of hydrogen. The large excess of hydrogen is needed to prevent coking in the reactor due to the high operating temperature. There is 4.8 lb-mol/hr of diphenyl produced. The highly exothermic reaction dominates, raising the temperature to 1222F.

The hot reactor effluent is quenched to 1130F by adding a cold liquid stream (also to prevent coking) in the mixer, M2. Mixer M2 combines the output of the PFR stream, Rout, with the cooling stream, quench. The quench stream is a portion of the product stream, liq. The bottom output of the separator, SEP, is the liquid product stream, liq. This stream, liq, is sent through pump P1, to the splitter, T1. T1 sends the liquid product through valve V3 to the distillation columns for further treatment (not shown). A portion of the product stream, liq, is sent up through valve V11, where it becomes the quenching fluid to bring the hot reactor product temperature lower.

The hot effluent stream coming out of the mixer, M2, is used to heat the incoming reactants mixture before it enters the furnace, thus giving up some of its heat content and cooling to 252F. Further cooling of this stream to 113F is by the simulated water driven heat exchanger, Cond, which has an output stream, qcond. This stream, qcond, controls the heat taken out of the product stream, and thus affects the temperature in the separator.

The liquid product stream, v3out, out the bottom is mostly benzene, with some

toluene and diphenyl. This product stream delivers 511 lb-mol/hr of product with the main constituents being benzene at 68%, and toluene at 26%. The gas stream, gas, is sent to a compressor and then to the splitter, T2. A purge stream, v4out, is taken of 60mol% methane and 40 mol% hydrogen. The rest of the gas (3990 lb-mol/hr) is recycled back to the front-end mixer. The purge stream is necessary to avoid excessive build-up of methane in the recycle stream back to the input mixer, M1.

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EXPERIMENTAL DETAILS

In HYSYS, the reactor design is implemented-see Figure1. Two kinetic expressions governing the process are:

;

R=rate in lb-mol/min-ft3

P: Pressure in psiaT: Temperature in Rankin

Activation energy constant: (90800 Btu/lb-mol)

R: Rate constant in Btu/lb-mol.Rankin

Subscripts B, H, T, and D are benzene, hydrogen, toluene, and diphenyl respectively

During investigation of the initial HYSYS design, it was found that the reactor volume and condenser had been re-sized. This small table updates the information reported during the initial Thesis proposal. All other parameters of the design remained the same (as reported Douglas): FEHE: 500 ft3, shell 500 ft3 in tubes

Reactor volume: 4065 ft3

Condenser: 1000 ft3

Separator: 80 ft3

The initial HYSYS design showed these specifications: Valves are sized at 50% open and 50 psi pressure drop. The compressor is run with constant work. Figure 2. shows the HDA reactor design with controllers added. Note that this figure is the same as Figure1, except the control loops have been added.

Figure 2. HDA reactor design with control loops

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Important control loop information (HYSYS initiation): 1) There are seven control loops:

Table1. Table of controllers in HDA design. Controller Control functionFC1 Fresh feed of toluene, toltotPCR Pressure of vessel SEPTCR Temperature of furnace, FurTCC Temperature of vessel SEPLC Level control of SEPCC Concentration (of methane) control, purge stream. TCQ Temperature of hot stream to heat exchanger, FEHE

2) Pressure control recorder (PCR) manipulates valve V1 to control separator drum pressure.

3) Gas purge is manipulated by controlling the methane composition in the recycle (CC). Xmtr: 40 to 70% methane.

4) Energy input to the furnace is maintained by varying the stream, qfur. Xmtr: 1100 to 1200F. This range was later extended in DeltaV.

Three things basically affect the pressure in this gas-filled system: fresh feeds, purge flow, and rate of condensation in the condenser. The flow rates of fresh hydrogen and of the purge gas stream are very close (484 and 476 lb-mol/hr respectively), however, purge rate has a direct impact on methane impurity in the gas recycle, so hydrogen feed controls the pressure.

The power to the compressor is a steady-state fixed value, so the gas circulation rate

through the gas loop is constant. Optimum values for reactor size and recycle flow rate are determined by balancing the reactor with the energy cost of compression.

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PROCEDURES

The project involves exploration of two software packages: HYSYS and DeltaV. The reactor process is implemented in HYSYS to take advantage of the physical and chemical parameters available to this software. The reactor process is later linked via OPC to the digital automation system, DeltaV, where the controllers will perform tests to optimize the response of each control loop (using many of the DeltaV advanced control features).

Initial OPC testing began with configuration of a simulated stream, similar to the “toltot” stream in Figure1. Once this “test” stream was successfully built and tested in HYSYS, the OPC pipelines were configured to enable communications with DeltaV. The test module was built in DeltaV’s Control Studio under an already working area. When it was found that successful operation of the communication had been attained, the entire process design conversion was begun.

DeltaV’s Control Studio is where the module is built, and all the parameters exist-such as: set points, output and input limits, alarms, control configurations, and the complete operating conditions. In this window, control blocks (or motors, alarms, valves, etc.) are imported from the drop down menu list on the right hand side of the window. The important control parameters, input and output, alarms, and operating modes are entered on the left hand side of the window. A large picture of Control Studio is available in the Appendix as Figure dV2. Figure dV2. Control Studio

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A new area was created in DeltaV’s Explorer section: HDA. The area represents a real scenario, where a physical portion of a plant is given a name (such as water treatment, gas compression, etc.). In this new area, the first controller to be built was FC1, the control of the toluene feed to the process. This stream had already been previously successfully modelled, so the same routine could be utilized in this first controller configuration.

The new controller was built from DeltaV’s extensive library of control modules-see Figure dV1-DeltaV Explorer window which features Library module templates and the newly built process area HDA. These modules contain building blocks for: analog control, monitoring, motors, and valves. For this thesis, only analog control building blocks were used. Analog control is further divided into: PID, FF, Cascade, fuzzy, and MPC modules. An appropriate module is loaded into the area, renamed, and then opened with Control Studio.

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Every controller’s starting parameters are based on the information pulled from the HYSYS dynamic simulation. These were entered into the Control Studio parameters with strict attention being paid to type of action of the controller (either Direct or Reverse acting), process variable connections and limits of measurement, controlled variable limits, and correct naming and references-see Figure dV2-typical Control Studio window featuring the CC controller configuration.

Each controller was entered into the HYSYS DCS interface window-see Figure H1-Process Variable (PV) imported information. In this window, PV Export sends information from the HYSYS environment to the DeltaV, and PV Import expects the control information, which it applies to the process. Although this figure represents the entire process converted, the interface was actually built one controller at a time.

When the first controller was built, HYSYS enabled the DCS interface, and then the process was run in dynamic mode, simulating an operating process. HYSYS has the flexibility of running the process faster or slower than real-time, an advantage that was used to monitor the process during controller optimization. In certain instances, running a process too fast caused the process to upset, and running the process too slow would require long wait times as the process responded to disturbances, updates, or changes.

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RESULTS AND DISCUSSION

A. Controller optimization results and analysis

The table shows the results of the many tests that were run on the process in the deltaV environment. Table 2. Results of controller optimization table.

Controller 1 2 3 4 5 6 7Name of controller FC1 LC TCC CC PCR TCR TCQHYSYS Control strategy

PI P PI P PI PI PI

dV control strategy PI PID PID Fuzzy PID Fuzzy PIDHYSYS Gain 0.3 2 0.5 2 2 0.5 4dV Gain 0.3 4 0.5 1.18 4 2.09 0.5HYSYS Integral 0.5 None 5 none 10 2.5 1.8dV Integral 0.5 2 5 20.42 12 1.66 40HYSYS Derivative None None none none none none nonedV Derivative None 1 1 0.44 2 0.21 10Action Rev. Dir. Dir. Dir. Rev. Rev. Dir.

Eventually a systematic pattern was developed for the testing and

optimization of each controller. As described earlier in the “Procedures”, controller FC1 transfer was undertaken first because it had successfully been rebuilt in a different area of the DeltaV Control Studio. Also, this controller has no upstream events, since it is an input stream. The OPC link is enabled (see Figure dV3 below) by hitting the enable button in the HYSYS DSC interface window.

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A small button, similar to a green traffic light, is depressed, thus putting the design into dynamic operations mode. If the process is operating correctly, the timer begins to count, and the HYSYS environment is minimized. In DeltaV, the control module is placed in the on-line mode, and by opening the AutoTune window, the process response can be followed. A typical AutoTune will look like:

Figure PCR1. PCR PID DeltaV control upon start-up in HYSYS.

AutoTune has a wealth of features: test capabilities of the process-which returns process parameters during a test, tuning calculations-where recommended settings can be updated, controller-where the settings of the controller are stored. Also, the three bottom lines in the tuning calculation,

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Gain, Reset, and Rate, can all be manually adjusted. Thus, one can over-ride the recommended settings.

In the above diagram, the output is oscillating, and the process variable (PV) is in an oscillating decay. Controller FC1 had a similar response upon start-up, using the initial dynamic settings from HYSYS. Controller FC1, which contains the input bulk toluene stream, needed no changes. Disturbances (set point, input flow) were initiated and the system responded well. AutoTune became the main tool in optimizing and controlling the HYSYS design. It was also very easy to use.

The second controller was LC. LC is controlling the output of the product stream, v3out. Simple PI control was not found to be the best choice. Initial transfer into the DeltaV (dV) system found negative pressure warnings, and ultimately froze the HYSYS simulation. Simultaneously, the system would then disrupt the parameters in the separation vessel, SEP. Using dV’s Tune features, the parameters from HYSYS were used as an initial starting point, and then the process parameters were changed until greater stability was reached. It was found that the valve, V3, would experience large fluctuations, rapidly opening and closing, thus the potential for extreme damage to the valve. Several PID tests were undertaken in AutoTune, with the final settings displayed in Table 2. It should be noted that initial PI control was expanded to PID. It was found that to achieve best response with the control loops, several tests should be taken and then parameters updated and accepted into the controller. The process was again allowed to stabilize to see how the response behaved. With each iteration of this process, superior control would be achieved.

TCC controls the temperature in the separation vessel. It was a logical choice to proceed with optimization of this controller after LC. Had I attempted optimization of TCC first, I most likely would have been re-starting HYSYS many times. The product stream, v3out, is very sensitive to changes in the flow and pressure in SEP. However, temperature control has less effect on v3out, and furthermore, if the vessel is large, then temperature takes a long time to adjust to new level. SEP is a mid-sized vessel, and its temperature does not vary at an alarming pace with upsets, so its optimization was a logical choice for TCC.

In HYSYS, a valve is implied in the control of the heat duty in the condenser, Cond. Thus, the feature of controlling the heat duty of the flow was mimicked in DeltaV. The output scale in DeltaV’s control studio compensated for the simulated valve by setting the controlled variable as the heat flow. (In HYSYS, the initial control was a valve with a 0 to 100% open setting). Initially TCC was run at the HYSYS settings, but it was found that only a one-degree setpoint change caused too much oscillation-solved by adding derivative action.

Derivative action measures the rate of change of a variable. Because the process was oscillating, the rate of change (slope) is large. By adding derivative action, it counters the movement by initiating a slope of opposite value. By varying the settings of the derivative, and monitoring the response

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in AutoTune, it was found that adding derivative control (i.e. rate) of 1 min, stabilized the loop. Derivative is a good addition to loops with temperature control, since the steadily changing temperature can be immediately compensated. Derivative setting would be even more important if the vessel was larger, but the rate setting would be less. Once this change had been made, the loop stabilized.

Since the vessel, SEP, has another controller, PCR, this was investigated next. The separator pressure is very sensitive to disturbances. Beginning with the initial settings from the dynamic state in HYSYS, the process was turned over to the DeltaV environment. Initial testing on the loop resulted in instability, so derivative action was added in a attempt to reduce the ramping nature of the valve. Many instances of backpressure, extreme valve swings, large oscillation in the condenser, and excessive pressure deviations from setpoint were encountered. This is because the separator is at the center of many other loops. When the pressure was too high or low, valve V3 would lock up and the process would shut down. Also, excessive pressure fluctuations would cause the process to freeze. Similarly, when temperature and pressure were changed, this would also disrupt the process.

To undertake tuning and optimization of this loop, dV’s AutoTune feature was used. Several tests had to be undertaken in this feature due to the loops instability. As the process was initialized in HYSYS, and then enabled, DeltaV would begin its attempt to control the system. Every so often the AutoTune feature was utilized to return some optimum settings. Using the update feature, the new controller settings were uploaded to the control strategy parameters back in the Control Studio. After each subsequent AutoTune, the process was allowed to reach its best state of stability. At this point, another test was run, returning a new set of controller parameters, which were also subsequently updated to the controller. Initial commencement of this iterative process was not met with great response by HYSYS. Because of the interactions back in the original process, the HDA process would repeatedly freeze if the parameters in the separator became too excessive. Occasionally, fluctuations in the separator would also cause other parts of the process to experience difficulties (the aforementioned valve V3, and the condenser, COND).

After several start-up sequences, each iteration would return a healthier response. Because of the interactions, the valve, V3, and its controller had to be re-tested for stability. Although Table 1. shows the final settings, the first run through of tests on this control loop did not return the listed parameters. It was only after seeing the separator fluctuations, that it was decided to go back and re-test the valve output, and adjust the control parameters for tightness. Once this had been achieved, the control of PCR seemed to be easier. With tighter control on the output product, the separator gained a bit of ease in controllability. Finally, a start-up test was taken on the control settings, and the new PCR responded within 10 minutes, bringing the process to set point with no fluctuations-see Appendix, Figure PCR1, which was also shown earlier.

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Upon transfer to DeltaV’s control system, controller CC showed severe oscillation-see Figure CC1. Figure CC1.

The appendix-Figure CC1 through CC5 shows the various figures, and ultimately the results of the solutions to controlling this part of the process. Several attempts were made to tune this loop with conventional PID, but since favourable results were not being attained, it was decided to investigate the potential of using a special feature of DeltaV: Fuzzy logic.

Fuzzy logic was primarily invented for use on noisy processes-where controlled variables and the process variables have large oscillatory tendencies. Three parameters, dE, error, and output (o/p), work together in a non-linear fashion. Thus the parameters can more accurately model the fluctuations of a noisy process. Since the parameters can more closely resemble the process, it was found to be advantageous for controller CC. A more in-depth description of Fuzzy logic control is in the Appendix addition-Fuzzy logic: How does it work?

Figure CC1 shows the results of some early testing on the loop. It was determined that any process optimization, set-point changes, or deviance testing in the process lines could not be initiated until the loop was properly tuned. The frequent oscillations evident in PID control began to disappear as the tuning parameters were updated in the fuzzy environment. Many tests were undertaken to understand the function of varying each parameter of fuzzy logic (see Appendix addition), and seeing the response. Figure CC2 and CC3 show how problems still existed even after new parameters were accepted. The usual cause of this is that other parts of the process were also responding to variances, so a continual testing and retesting procedure was adopted. After several AutoTune test procedures, and a couple of re-starts of the process, Figure CC4 shows the final acceptable settings. Figure CC5 clearly shows that the fuzzy logic control was the correct choice for control of the process. The result of using this advanced feature of DeltaV resulted in optimum performance on the loop.

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Figure CC4. Fuzzy logic returns decent control.

The next two loops each contained lags in their design, to more closely represent a real process. A lag in a system occurs when there is a time delay in which the system can respond to a change. Fortunately, DeltaV easily handled this, by having programmable function blocks that serve as delay units. The only real difficulty was in trying to understand how to enter the parameters correctly in the function blocks. TCQ is a temperature control loop on the pre-heating product solution recycle line. It controls the valve, V11, where the quench liquid from the separator is just about to enter the mixer, M2, immediately after the plug flow reactor (PFR). Implementation of this loop was far easier than some of the earlier loops. Again using DeltaV’s AutoTune, along with changing and updating parameters, the transfer to control in the DeltaV environment was efficient. Figures TCQ1 and TCQ2 recorded the testing procedures and graphed the resulting control. Figure TCQ4 shows the block diagram design in Control Studio.

The final loop presented several challenges. The TCR loop was extremely noisy-see Figure TCR1.

Figure TCR1. Initial PID attempts at control. Various PID settings were tried and the resulting display shows the difficulties in obtaining reasonable control.

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After several trial tests in PID configuration, the interactions in the process were simply too much for conventional control. The main reason for all the interaction at this point in the process is that the control of temperature here changes the kinetic expressions, which in turn alter the production of benzene. This alteration in the temperature in the furnace produces either more or less benzene, which requires that the purge line, at valve V4, also changes at a rapid rate. Included in this part of the process is the difficulty of the temperature signal delay. The temperature is measured at the input to the plug flow reactor, but by the time the heat stream can make compensations in the furnace, the temperature has appreciably been altered.

Due to the noise in the system, it was decided to once again utilize the fuzzy logic option available in DeltaV. The lag block module in Control Studio was used to module the time delay. The controlled variable is qfur, the heat to the furnace. TCR incorporated all the new techniques that had been utilized up to this point-it would have been difficult had the attempt been made to first try to control this section of the plant.

Several PID tests were undertaken in TCR, but none returned optimal control. Figure TCR1 shows the results of several PID parameter trials. This Figure shows the large oscillations and the difficulty that was experienced in

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trying to control the process. Figure TCR2 shows the initial transfer into the fuzzy logic environment. It is evident that the fuzzy logic control algorithms smoothed out the transitions. With experience gained from previous control attempts in fuzzy, and with DeltaV’s AutoTune feature, the process was under control after only a few iterations of the AutoTune feature. Figure TCR3 shows the final results of the optimization process. Figure TCR4 shows the Control Studio module. The lead/lag block is above the fuzzy logic control module, FLC. At this point, the entire process has been updated to control by the DeltaV environment.

A sensitivity test was taken on the TCR/CC controller configurations. It was identified earlier that the furnace temperature affected the rate of the reaction, and hence the residual amount of methane in the stream, v4out. Two recently generated AutoTune windows follow this page: Figure CC_TCR1 and Figure CC_TCR2. The first figure displays set point changes from 1250 to 1200 to 1150 and then back up to 1200F. The spike in the diagram is the controlled variable, qfur, as it responds to a 50F set point change. Because of the fuzzy logic control, the process variable slowly moves to the new set point with no oscillation-a very desirable result. In practice, it may be difficult to achieve such a large demand on the heat duty line, qfur. Still, the control of the upset is excellent.

It was expected that the response of CC would also be adequate, but there was much more volatility, with the process variable requiring more time to return to setpoint and with more oscillation. CC had previously been identified as a troublesome loop because the control is on the methane fraction in this purge line. These two loops were identified as being the most interactive of several combinations.

Figure CC_TCR1. Process response due to interaction. Setpoint of furnace changed from 1250 to 1200 to 1150 to 1200F.

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Figure CC_TCR2. Response of CC loop due to furnace temperature setpoint changes.

A test such as this is one of many that could be undertaken in the plant to view the response of the system. For instance, it may be desired to not have the TCR controlled variable, qfur, spike as much as it did in Figure CC_TCR1. If this was the case, then one could go back and perform tests to change the control parameters to optimize the control of the heat input. Also, if the desire for larger heat production has been identified, one could go back to HYSYS and modify the heat supply. Similarly, the CC could also be

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retested, as was previously done for even tighter control. As it stands, the response to the setpoint by the CC controller was acceptable, with a decaying oscillatory response. Also, the response returned to setpoint within one oscillation. One other alternative that could be investigated is whether a larger valve would be of benefit to the purge stream. A large valve would be beneficial if the process was desired to be run at a higher operating temperature, producing more benzene. This large valve could be implemented in HYSYS and more testing undertaken.

An optimization study was done. As in the previous discussion, it is known that the temperature of the furnace affects the reaction rates, and hence the benzene production.

Table 3. Product stream compositions at different furnace temperatures. Furnace temperature= 1150 F 1200 F 1250 FH2 0.0052 0.0047 0.0047CH4 0.0442 0.0437 0.0431Benzene 0.6808 0.8731 0.8861Toluene 0.2589 0.0334 0.0006Diphenyl 0.0109 0.045 0.0654

It can be seen what the effect of raising the furnace temperature would be on the production of benzene. With DeltaV in control of the process, these tests took place with no upsets. From a purely production standpoint, even though benzene production is increased with increased furnace temperature, other undesirable conditions surfaced. Diphenyl production continues to increase as furnace temperature increases, causing the undesirable condition of more stringent distillation of the product stream. An increase in temperature from 1200 to 1250F only increased the production of benzene slightly, but Diphenyl production increased from 4.5% to 6.5%. As a consequence of this increased heat demand, the stream, qfur, to the furnace increased to 31.3e6 Btu/hr from 7.03 e6 for a 100F increase. Also, the condenser before the separator is now removing 37.7e6 Btu/hr as compared to a previous value of 13.4e6 Btu/hr. So the trade-off of increased production of benzene is increased energy costs. Also, with Diphenyl production increasing, this causes more strain on the downstream unit operations.

Several such analysis tests could further be performed on other parts of the process to see if more benefit would be gained in another area. Test after test could be performed, depending on economic factors, to find the optimum operating conditions. However, control of the process, as was the objective of this thesis has been achieved through the integration of the HYSYS/DeltaV environments using the OPC communications links.

CONCLUSION

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1) The two-tier system of DeltaV/HYSYS could be very useful in analyzing a new process. The process is developed in HYSYS, where calculations return the static operating conditions. Further changes can be made in HYSYS as the design becomes updated. The OPC link between the two software packages provides access to DeltaV’s advanced control strategies. This two-tier development allows all of the simulations and controls to be configured long before any actual construction begins. Further, process improvements may be realized by using the two-tier system, or the process could be discontinued if the feasibility studies show that an economic assessment did not show a reasonable rate of return.

2) Once optimum control is achieved, disturbances and set point changes can show where the process may need to be re-evaluated. This would be an ongoing feasibility study known as process optimization.

3) Developing a process in HYSYS in static mode returns acceptable results. HYSYS dynamic control was to found to have low reproducibility, hence the need for the integration of controls from DeltaV. HYSYS was found difficult to use, and requires much patience.

4) DeltaV was found to be much easier to use than HYSYS. DeltaV is very well supported by on-line information, vendor assistance, and software driven help files. DeltaV’s dynamic control functions, controller configurations, and advanced techniques are user-friendly.

5) The HDA process received a sensitivity analysis. It was found that after transfer to the controllers in DeltaV that tests were much easier to perform. After the optimization of all the controllers had been performed, the sensitivity analysis showed the improved controllability.

6) It was identified early in the research that the reaction temperature was the main driving force in the production rate of benzene from toluene. An increase in furnace temperature increased the production rate of benzene, but at the cost of increased heat energy input and removal. Also, increases in furnace temperature increased the production of the unwanted by-product, Diphynel. In order to completely analyze this process, an acceptable level of production would have to be economically weighed against the cost of the energy requirements as well as the increased cost of removing the by-product further down the line at the distillation area.

RECOMMENDATIONS FOR FURTHER STUDY

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There are three main areas for further research: the HDA process, DeltaV, and HYSYS.

The book by James M. Douglas, “Conceptual design of chemical processes”, has extensive strategies and insight into optimizing every part of the hydrodealklyation of Toluene. For example, the reactor temperature is a critical part of the design. From Douglas it is known that temperatures above 1300F cause a significant amount of hydrocracking. At temperatures below 1150F, the reaction rates become too slow. Some time was spent learning how to use HYSYS, but possibly some optimization could have been done by using some of the suggestions in Douglas, and trying to implement the ideas in HYSYS. The only drawback is that HYSYS requires many hours of study to make processes work properly. Indeed, much of the early part of this thesis was spent understanding how HYSYS works. HYSYS, however, is a powerful tool, which delivers valuable information.

The DeltaV digital automation system is a very large integrated software package. In this thesis, some optimization of the design was obtained by communications via OPC to HYSYS, but several other techniques are yet to be explored in DeltaV. A great deal of computing power is needed to run the HYSYS program; therefore, the graphics could be rebuilt in the DeltaV. The entire process could be rebuilt with completely different graphics. (Note: a graphical interface was later added)

DeltaV can be configured solely for operate interface. These operator interfaces present plant operators with faceplates showing the controller, and the ability to change setpoints, or investigate other important information about the process-see Figure TCQ3. In the DeltaV Operate window, no parameter changes can be made.

But much more important is the controls available through DeltaV, of which only a few where used in this thesis. Of particular note, is the MPC control on the SEP section, where this control might have been advantageous.

Further study could contain an economic analysis to see if the feasibility of continued production is warranted.

LITERATURE CITED

Douglas, James, Conceptual design of chemical processes, McGraw-Hill, New York, 1988DeltaV Product Information Compact Disc, produced by Fisher-Rosemount, Austin, Texas, 2001Luyben, William L, Plantwide dynamic simulators in chemical processing and control, Marcel Dekker Inc., New York, 2002

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Figure HDA1. static results, workbook copy in english units

Name FFH2 v1out v2out cin Rgas coutVapour Fraction 1.00 1.000 0.000 0.918 1.000 1.000Temperature [F] 86.00 86.133 131.433 145.958 160.378 1062.368Pressure [psia] 625.00 600.512 600.512 600.512 600.512 564.684Molar Flow [lbmole/hr] 484.31 484.311 369.964 4840.822 3986.547 4840.822Mass Flow [lb/hr] 1180.17 1180.173 34088.436 79101.556 43832.947 79101.556Heat Flow [Btu/hr] -427686.49 -427686.49 2728353.29 -66806697.27 -69107364.08 -4430563.00Comp Mole Frac (Hydrogen) 0.97 0.970 0.000 0.440 0.417 0.440Comp Mole Frac (Methane) 0.03 0.030 0.000 0.473 0.570 0.473Comp Mole Frac (Benzene) 0.00 0.000 0.000 0.009 0.011 0.009Comp Mole Frac (Toluene) 0.00 0.000 1.000 0.078 0.002 0.078Comp Mole Frac (BiPhenyl) 0.00 0.000 0.000 0.000 0.000 0.000Name hot in hot out Rin Rout quench totVapour Fraction 1.000 0.980 1.000 1.000 0.000 1.000Temperature [F] 1129.061 252.058 1150.000 1221.607 113.664 1129.151Pressure [psia] 504.038 472.393 521.038 504.038 504.038 504.038Molar Flow [lbmole/hr] 4974.232 4974.232 4840.822 4840.822 135.110 4975.932Mass Flow [lb/hr] 89820.708 89820.708 79101.556 79100.530 10735.002 89835.531Heat Flow [Btu/hr] 4316715.17 -58059419.10 2228994.86 2228984.85 2220202.54 4449187.38Comp Mole Frac (Hydrogen) 0.375 0.375 0.440 0.386 0.005 0.375Comp Mole Frac (Methane) 0.516 0.516 0.473 0.529 0.045 0.516Comp Mole Frac (Benzene) 0.080 0.080 0.009 0.063 0.687 0.080Comp Mole Frac (Toluene) 0.028 0.028 0.078 0.022 0.250 0.028Comp Mole Frac (BiPhenyl) 0.001 0.001 0.000 0.001 0.013 0.001Name condout Gas liq dischg grecycle purgeVapour Fraction 0.8971 1.0000 0.0000 1.0000 1.0000 1.0000Temperature [F] 113.0258 113.0258 113.0258 160.3782 160.3782 160.3782Pressure [psia] 469.1770 469.1770 469.1770 600.5119 600.5119 600.5119Molar Flow [lbmole/hr] 4974.2317 4462.3765 511.8552 4462.3765 3986.5469 475.8296Mass Flow [lb/hr] 89820.7084 49064.7989 40755.9095 49064.7989 43832.9492 5231.8497Heat Flow [Btu/hr] -70725461.74 -79078108.19 8352646.44 -77355939.99 -69107365.50 -8248574.49Comp Mole Frac (Hydrogen) 0.3746 0.4170 0.0049 0.4170 0.4170 0.4170Comp Mole Frac (Methane) 0.5163 0.5705 0.0437 0.5705 0.5705 0.5705Comp Mole Frac (Benzene) 0.0798 0.0109 0.6800 0.0109 0.0109 0.0109Comp Mole Frac (Toluene) 0.0280 0.0016 0.2586 0.0016 0.0016 0.0016Comp Mole Frac (BiPhenyl) 0.0013 0.0000 0.0128 0.0000 0.0000 0.0000Name v4out Pump o/p fquench FF Toluene v11out ProductVapour Fraction 1.000 0.000 0.000 0.000 0.000 0.000Temperature [F] 158.788 113.484 113.484 130.946 113.678 113.484Pressure [psia] 475.000 544.000 544.000 696.896 504.000 544.000Molar Flow [lbmole/hr] 475.830 511.855 135.110 369.964 135.110 376.745Mass Flow [lb/hr] 5231.850 40755.910 10758.006 34088.436 10758.006 29997.903Heat Flow [Btu/hr] -8248574.49 8366979.86 2208563.72 2728353.29 2208563.72 6158416.14Comp Mole Frac (Hydrogen) 0.417 0.005 0.005 0.000 0.005 0.005Comp Mole Frac (Methane) 0.570 0.044 0.044 0.000 0.044 0.044Comp Mole Frac (Benzene) 0.011 0.680 0.680 0.000 0.680 0.680Comp Mole Frac (Toluene) 0.002 0.259 0.259 1.000 0.259 0.259Comp Mole Frac (BiPhenyl) 0.000 0.013 0.013 0.000 0.013 0.013Name Final Product Qfur Q from Cond Work to Comp work to pump Vapour Fraction 0.0000 <empty> <empty> <empty> <empty> Temperature [F] 113.6780 <empty> <empty> <empty> <empty> Pressure [psia] 504.0000 <empty> <empty> <empty> <empty> Molar Flow [lbmole/hr] 376.7450 <empty> <empty> <empty> <empty> Mass Flow [lb/hr] 29997.9031 <empty> <empty> <empty> <empty> Heat Flow [Btu/hr] 6158416.14 6659557.86 12666042.64 1722168.20 14333.42 Comp Mole Frac (Hydrogen) 0.0049 <empty> <empty> <empty> <empty> Comp Mole Frac (Methane) 0.0437 <empty> <empty> <empty> <empty> Comp Mole Frac (Benzene) 0.6800 <empty> <empty> <empty> <empty> Comp Mole Frac (Toluene) 0.2586 <empty> <empty> <empty> <empty> Comp Mole Frac (BiPhenyl) 0.0128 <empty> <empty> <empty> <empty>

Late evening, Jan 13

Figure dV1. DeltaV Explorer

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Figure dV2. DeltaV Control Studio

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Figure dV3. HYSYS/DeltaV OPC DSC interface window, in HYSYS environment.

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Figure PCR1. PCR PID DeltaV control upon start-up in HYSYS.

Figure CC1. Initial fuzzy logic implementation.

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Figure CC2. Changes in fuzzy logic parameters attempted.

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Figure CC3. Continued testing of fuzzy logic.

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Figure CC4. Fuzzy logic begins to return decent control. AutoTune process test at 17:03.

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Process was run at 2, .25, .25 from an initial wide open valve. Process came up to a stable oscillation. Tests run at 17:03 results in test process returning recommended scaling parameters. The final test process (the test process can be seen on the bottom left hand part of the screen, which tests for ultimate gain, period, dead time, process gain, and time constant). The recommended scaling settings are updated to the controller and then uploaded in Control Studio.

Figure CC5. Fuzzy logic returns optimal control.

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Parameters accepted by upload/download in DeltaV.

Figure TCQ1. TCQ testing.

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Figure TCQ2. Completed testing on TCQ loop, with final testing parameters accepted.

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Figure TCQ3. dV Operator Interface window

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Figure TCQ4. Lag implementation on TCQ

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