1

CHAPTER ONE

INTRODUCTION

1.1 Background of the work

The connections between the units of a chemical processing plant are important

because the behaviour of a complete processing plant is not only given by its

individual units. Though if the units of a plant are connected in series, it is easy to

predict the behaviour of a plant from the behaviour of the individual units, this does

not imply that the units can be operated like individual units. The output of one unit

will act as a disturbance to the other unit; to the extent that for even a system with

simple connection, certain considerations need a perspective above the unit operation.

The issue of plant-wide control seeks to answer the question of how to combine the

controllers of the different unit together.

For instance the presence of mass recycle and heat integration changes the dynamic

and steady state behaviour of the plant in ways that are difficult to predict from the

behaviour of the individual units so that heat integration and mass recycle call for a

plant-wide perspective of control structure design. Plant-wide control simply put,

refers to integrating the controllers of different units of a plant (Larsson, 2000).

A better understanding of plant-wide control will lead to better design of control

system. Better control system will give plants lower energy consumption and better

utilization of raw materials. This is good for the society and the industry. The

realization that the field of control structure design is underdeveloped is not new. In

the 1970s several articles were written on the gap between theory and practice in the

area of process control. The most famous is the one of (Foss, 1973) who made the

observation that in many areas application was ahead of theory and he stated that the

2

central issues to be resolved by the new theories are the determination of the control

system structure, which variables should be measured, which inputs should be

manipulated and which links should be made between the sets. The gap is indeed

present but on a contrary view, the theoretician must close it. Many authors have

pointed out that the need for a plant-wide perspective in control is mainly due to

changes in the way plants are designed with more heat integration, recycle and less

inventory. Indeed, these factors lead to more interactions and therefore the need for a

perspective beyond individual units. However even without any heat integration, there

is still a need for a plant-wide perspective as a chemical plant consists of units

connected in series and one unit will act as a disturbance to the next one.

The design of a typical plant-wide control structure consists of four major steps:

1. The overall specification for the plant and its control system are stated

2. The control system structure is developed. These steps involve :

i. Selection of controlled outputs ( variables with setpoints )

ii. Selection of manipulated inputs

iii. Selection of control configuration (a structure interconnecting

measurements/set points and manipulated variables)

iv. Selection of controller type

3. Design is followed by a detailed specification of all instrumentation/hardware and

software, cost estimation, evaluation of alternatives and the ordering and installation

of equipment.

4. Following design and construction of the plant, plant tests including start-ups,

operation at design conditions and shut downs are carried out prior to commissioning

of the plant.

3

1.2 Objectives

The control objectives for this process are typical for a chemical process;

1. Maintain process variables at desired values.

2. Keep the process operating conditions within equipment constraints

3. Minimize variability of product rate and product quality during disturbances

4. Minimize movement of valves which affect other processes

5. Recover quickly and smoothly from disturbances, production rate changes or

product mix changes

6. Tune controllers to determine the parameters for the control loops of the

process plants using the auto-tuning approach in the ASPEN DYNAMICS

simulator.

1.3 Scope of the Work

This work focuses on the plant-wide control of hydrodealkylation (HDA) process. The

Control application for this work will utilize the first two steps highlighted earlier in

the background of the work.

1.4 Justification for the research

The behaviour of a complete Chemical processing Plant is not given by its individual

units, the connections between the units are equally important. The behaviour of a

Plant with units connected in series is easy to predict from the behaviour of the

individual units. This does not imply that the units can be operated like individual

units. The output of one unit will act as disturbance on the next unit and at steady-

state; they must have the same through-put. For a system with simple connection,

certain considerations need a perspective above the unit operation. An example is the

4

placement of level controllers for a Plant with units in series. It is exactly such a type

of structural question that the field of Plant-wide control seeks to answer. In addition,

the presence of heat integration and mass recycle changes the dynamic and steady-

state behaviour of the Plant in ways which are difficult to predict from the behaviour

of the individual units. Therefore heat integration and mass recycle makes the need for

a Plant-wide perspective much more pronounced when the control structure is

designed. A better understanding of Plant-wide control will however lead to a better

design of control system.

The control structure design problem is difficult to define mathematically both

because of the size of the problem and the large cost involved in making a precise

problem definition which would include e.g. a detailed dynamic and steady state

model. An alternative to this is to develop heuristic rules based on experience and

process understanding. This is what will be referred to as the process oriented

approach.

5

CHAPTER TWO

LITERATURE REVIEW

2.1 Definition of plant-wide control

A chemical plant may have thousands of measurements and control loops. By the term

plant-wide control it is not meant the tuning and behaviour of each of these loops, but

rather the control philosophy of the overall plant with emphasis on the structural

decisions. The structural decision include the selection/placement of manipulators and

measurements as well as the decomposition of the overall problem into smaller sub-

problems (Larsson, 2000). One could imagine using a single optimizing controller

which will stabilize the process and at the same time can perfectly co-ordinate all

manipulated inputs based on dynamics optimization but this will not be the best

because a feedback control is better done locally than globally.

Since plant-wide control is about controllers, very important (perhaps the most

important) problem is the issue of determining the control structure. Control structure

design is defined as the structural decisions involved in control system design,

including the following task:

1. Selection of controlled outputs (variable without set points)

2. Selection of manipulated inputs

3. Selection of measurements (for control purposes including stabilization)

4. Selection of control configuration (a structure interconnecting

measurements/set points and manipulated variables)

5. Selection of controller type.

6

In most cases, the control structure design is solved by:

a. Consideration of control objectives.

b. Determination of which degree of freedom are available to meet the task 1 and

2 above.

c. A bottom-up design of the control system to stabilize the process to perform

the tasks 3, 4, and 5 above.

2.2 History of plant-wide control

The first comprehensive discussion on plant-wide control was given by Buckley

(1964). The chapter introduces the main issues, and presents what is still in many

ways the industrial approach to plant-wide control. Some of the terms which are

introduced and discussed in the chapter are material balance control( in the direction

of flow and in the direction opposite of flow), production rate control, and buffer

tanks as low-pass filters, indirect control, and predictive optimization. He also

discusses recycle and the need to purge impurities. In summary, he presents a number

of useful engineering insights; there is really no overall procedure (Larsson, 2000).

2.3 Design questions in plant-wide control

If we consider a general process with several inputs and outputs, several questions

must be answered before we attempt to design a control system for such a process,

some of which are discussed below:

1. What are the control objectives? In other words, how many and which of the

possible variables should be controlled at desired set point? This is very

critical for the design of the efficient control systems.

7

2. What outputs should be measured? Once the control objectives have been

identified we need to select the measurements necessary to monitor the

operation of the process. The measured output can either be primary

measurements (output through which we can determine directly if the control

objectives are satisfied) or secondary measurements (measurements that are

not used to monitor directly the control objectives but are auxiliary

measurements employed for cascade, adaptive, or inferential control).

3. What inputs can be measured? Worth knowing is the manipulative variables

can be measured and therefore can be employed for any kind of control. With

respect to the disturbances, only a few can be measured easily, rapidly, and

reliably. These measured disturbances can be used to construct feed forward,

feedback, feed-forward-feedback, and ratio control configurations.

4. What manipulated variables should be used? A multiple-input, multiple-output

system possesses several manipulated variables which can be used for the

design of a control system. The selection of the most appropriate manipulation

is crucial and should be carefully approached. Some manipulations have a

direct, fast and strong effect on the controlled outputs; others do not.

Furthermore, some variables are easy to manipulate in real life (e.g. liquid

flow); others are not (e.g. flow of solids, slurries etc.).

5. What is the configuration of the control loops? Once all the possible

measurements and manipulations have been identified, there is a need to

decide how they are going to be interconnected through the control loops. In

other words, what measurements will actuate a given manipulated variable or

what manipulation will be used to regulate a given controlled output at its

desired value? For a plant-wide case, there is a large number of alternatives

8

control configurations. The selection of the most appropriate is the central and

critical question to be resolved.

2.4 Previous work on the HDA process

Stephanopoulos (1984) followed the approach proposed by Buckley (1964) based on

material balance and product quality control. He used an HDA plant model where

steam is generated from the effluent of the feed effluent heat exchanger through a

series of steam coolers. From the material balance viewpoint, the selected controlled

variables of choice were fresh toluene feed ow rate (production rate control), recycle

gas ow rate, hydrogen contents in the recycle gas, purge owrate, and quencher ow

rate. Product quality is controlled through product compositions in the distillation

columns and the controlled variables selected are product purity in benzene column

and reactor inlet temperature. Later, Douglas (1988) used another version of the HDA

process to demonstrate a steady-state procedure for owsheet design. Brognaux

(1992) implemented both a steady-state and dynamic model of the HDA plant in

SpeedupT M

based on the model developed by Douglas (1988) and used it as an

example to compute operability measurements, dene control objectives, and perform

controllability analysis. He found that it is optimal to control the active constraints

found by optimization.

Wolff (1994) used an HDA model based on Brognaux (1992) to illustrate a procedure

for operability analysis. He concluded that the HDA process is controllable provided

the instability of the heat-integrated reactor is resolved. After some additional

heuristic consideration, the controlled variables were selected to be the same as used

by Brognaux (1992).

Ng and Stephanopoulos (1996) used the HDA process to illustrate how plantwide

control systems can be synthesized based on a hierarchical framework. The selection

9

of controlled variables is performed somehow heuristically by prioritizing the

implementation of the control objectives. In other words, it is necessary to control the

material balances of hydrogen, methane and toluene, the energy balance is controlled

by the amount of energy added to the process (as fuel in the furnace, cooling water,

and steam), production rate, and product purity.

Cao et al. used the HDA process as a case study in several papers, but mainly to study

input selection, whereas the focus of the present paper is on output selection. In Cao

and Biss (1996), Cao and Rossiter (1997), Cao et al. (1997a), and Cao and Rossiter

(1998) issues involving input selection are discussed. Cao et al. (1997b) considered

input and output selection for control structure design purposes using the singular

value decomposition (SVD). Cao et al. (1998a) applied a branch and bound algorithm

based on local (linear) analysis. All the papers by Cao et al. utilize the same

controlled variables selected heuristically by Wolff (1994). Cao et al. (1998b) discuss

the importance of modelling in order to achieve the most effective control structure

and improves the HDA process model for such purpose.

Ponton and Laing (1993) presented a unied heuristic hierarchical approach to

process and control system design based on the ideas of Douglas (1988) and used the

HDA process throughout. The controlled variables selected at each stage are: Toluene

ow rate, hydrogen concentration in the reactor, and methane contents in the

compressor inlet (feed and product rate control stage); separator liquid stream outlet

temperature and toluene contents at the bottom of the toluene column (recycle

structure, rates and compositions stage); and separator separator pressure, benzene

contents at stabilizer overhead, and toluene contents at benzene column overhead are

related to product and intermediate stream composition stage. The stages related to

energy integration and inventory regulation do not cover the HDA process directly, so

10

no controlled variables are assigned at these stages. Luyben et al. (1998) applied a

heuristic nine-step procedure together with dynamic simulations to the HDA process

and concluded that control performance is worse when the steady-state economic

optimal design is used. They chose to control the inventory of all components in the

process (hydrogen, methane, benzene, toluene, and diphenyl) to ensure that the

component material balance are satised; the temperatures around the reactor are

controlled to ensure exothermic heat removal from the process; total toluene ow or

reactor inlet temperature (it is not exactly clear which one was selected) can be used

to set production rate and product purity by the benzene contents in the benzene

column distillate. Luyben (2002) uses the rigorous commercial owsheet simulators

HysysT M

, Aspen PlusT M

and Aspen DynamicsT M

to propose a heuristic-based control

structure for the HDA process. Herrmann et al. (2003) consider the HDA process

to be an important test-bed problem for design of new control structures due to its

high integration and non-minimum phase behavior. They re-implemented Brognaux

(1992)s model in Aspen Custom ModelerT M

and design a model-based, multivariable

controller for the process. They considered the same controlled variables used by

Wolff (1994).

Konda et al. (2005) used an integrated framework of simulation and heuristics and

proposed a control structure for the HDA process. A HysysT M

model of the plant was

built to assist the simulations. They selected fresh toluene feed ow rate to set

production rate, product purity at benzene column distillate to fulfil the product

specication, overall toluene conversion in the reactor to regulate the toluene recycle

loop, ratio of hydrogen to aromatics and quencher outlet temperature to fulll process

constraint, and methane contents in the purge stream to avoid its accumulation in the

process. Table 1 summarizes the selection of (steady-state) controlled variables by

11

various authors. It seems clear that the systematic selection of controlled variable for

this plant has not been fully investigated although the process has been extensively

considered by several authors. In this work, a set(s) of controlled variables for the

HDA process is to be systematically selected.

12

13

2.5. Control Structure Design

The term Control structure design which is commonly used in the control community

refers to the structural decisions in the design of the control system. It is defined by

five tasks given in the background study:

1. Selection of controlled outputs (variables with set points )

2. Selection of manipulated inputs

3. Selection of measurements

4. Selection of control configuration

5. Selection of controller type

The result from the control structure design is the control structure alternatively

denoting the control strategy or control philosophy of the plant. Rinards and Downs

(1992) refer to the control structure design problem as defined above as the strict

definition of plant-wide control as they point out that plant-wide control also

includes important issues such as the operator interaction, grade-change, shut-down,

fault detection, performance monitoring and design of safety and interlock systems.

This is more in line with the discussion by Stephanopoulos (1982).

2.5.1 The Mathematical Oriented Approach

There are some methods which use structural information about the plant as a basis

for control structure design. Central concepts are structural state controllability,

observability and accessibility. Although the structural methods are interesting, they

are not quantitative and usually provide little information concerning insights about

the structure of the process that most Engineers already have. The control structure

design problem is difficult to define mathematically, both because of the size of the

problem, and the large cost involved in making a precise problem definition which

14

would include, for example a detailed and steady state model. Also, numerical criteria

used in the analysis are a limited and indirect reflection of the true design goals and

finally, constraints and abnormal conditions are not considered (Ricker 1995).

2.5.2 The Process Oriented Approach

An alternative to the mathematical approach is the process oriented approach which

involves developing heuristic rules based on experience and process understanding.

These procedures for Plant-wide control are based on using process insights that is,

methods unique to process control. The first comprehensive discussion on plant-wide

control was given by Buckley in his book Techniques of process control in a

chapter on Overall Process control (Buckley 1964). The chapter introduces the main

issues and presents what is still in many ways the industrial approach to plant-wide

control. Some of the terms which were introduced and discussed in this chapter are

material balance control (in direction of flow and direction opposite of flow),

production rate control, indirect control and predictive optimization. He also discusses

recycle and the need to purge impurities. He pointed out that one cannot control at a

given point in a plant inventory (level, pressure) and flow independently since they

are related through the material balance. In summary, he presents a number of useful

engineering insights but there are no overall procedures. Ogunnaike (1995) pointed

out that the basic principles applied by the industry do not deviate far from Buckleys

(1964) principles. Wolff and Skogestad (1994) review previous work on plant-wide

control with emphasis on the process-oriented decomposition approaches. They

suggested that plant-wide control system design start with a top-down selection of

controlled and manipulated variables and proceed with a bottom-up design of the

control system for both regulatory and stabilization purposes. This follows the steps 2

15

and 3 earlier stated in the previous subsection. At the end of the paper, ten heuristic

guidelines for plant-wide control were listed.

2.5.3 Selection of Controlled Outputs

The issue of selection of controlled outputs is probably the least studied of the tasks in

the control structure design problem. In fact, it seems from experience that most

people do not consider it as being an issue at all. The most important reason for this is

probably that it is a structural decision for which there has not been much theory.

Therefore the decision has mostly been based on engineering insight and experience

and the validity of the selection of controlled outputs has seldom been questioned by

the control theoretician. Questions like why are we controlling hundreds of

temperatures, pressures and compositions in a Chemical Plant, when there is no

specification on most of these variables confirms that the selection of outputs is

indeed an issue. Thinking through, one realizes that the main reason for controlling all

these variables is that one needs to specify the available degrees of freedom in order

to keep the plant close to its optimal operating point. A follow-up question therefore

comes forth Why do we select particular set of controlled variables? (e.g. why

control the top composition in a distillation column, which does not produce final

products rather than just specifying its reflux).The answer to this question is less

obvious because at first it seems like it does not really matter which variables we

specify (as long as all degrees of freedom are consumed because the remaining

variables are then uniquely determined). However, this is true only when there is no

uncertainty caused by disturbances and noise (signal uncertainty) or model

uncertainty. When there is uncertainty, then it does make a difference how the

solution is implemented i.e., which variables we select to control at their set points.

16

2.5.4 Selection of Manipulated inputs

By manipulated inputs we refer to the physical degrees of freedom typically the valve

positions or electric power inputs. Selection of these variables is usually not much of

an issue at the stage of control structure design since these variables usually follow as

direct consequence of the design of the process itself. This is because by definition,

the input variables are physical variables that affect the output variables. It is however

convenient to divide the input variables into manipulated variables that can be

adjusted and disturbance variables that are determined by the external environment.

Typically, input variables are associated with inlet streams (e.g. feed composition or

feed flow rate). Common disturbance variables include the feed conditions to a

process and the ambient temperature. Based on the Plant and control objectives, a

number of guidelines have been proposed for the selection of manipulated variables

from among the inputs variables (Hougen, 1979; Newell and Lee, 1989) and these are:

1. Select inputs that have large effects on controlled variables. For conventional

feedback control system, the manipulated variables should have a significant,

rapid effect on only one controlled variable thus having a corresponding large

steady state gain.

2. Choose inputs that rapidly affect the controlled variables.

3. The manipulated variables should affect the controlled variables directly rather

than indirectly.

4. Recycling of disturbances should be avoided: It is preferable not to manipulate an

inlet stream or a recycle stream to avoid disturbances being propagated or recycled

back to the system

17

2.5.5. Selection of Control Configuration

The control configuration is the structure of the controller that interconnects the

measurements, set points and manipulated variables. The controller can be

decomposed into a decentralized control structure. The controller is decomposed for

so many reasons among which are:

1. It may require less computation

2. Failure tolerance and;

3. The ability of local units to act quickly to reject disturbances (Findeisen et al.,

1980).

Skogestad and Hovd (1995) pointed out that the most important reasons are;

4. To reduce the cost involved in defining the control problem and setting up the

detailed dynamic model which is required in a centralized system with no

predetermined links.

5. Decomposed control systems are much less sensitive to model uncertainty

since they often use no explicit model.

2.6 HDA process description

The HDA process (Figure 1) was rst presented in a contest which the American

Institute of Chemical Engineers arranged to nd better solutions to typical design

problems (Mc Ketta, 1977). It has been exhaustively studied by several authors with

different objectives, such as steady-state design, controllability and operability of the

dynamic model and control structure selection and controller design.

The reactor effluent is quenched by a portion of the recycle separator liquid ow to

prevent coking, and further cooled in the FEHE and cooler before being fed to the

vapor-liquid separator. Part of the vapor containing unconverted hydrogen and

18

methane is purged to avoid accumulation of methane within the process while the

remainder is compressed and recycled to the process. The liquid from the separator is

processed in the separation section consisting of three distillation columns. The

stabilizer column removes small amounts of hydrogen and methane in the overhead

product, and the benzene column takes of the benzene product in the overhead.

Finally, in the toluene column, unreacted toluene is separated from diphenyl and

recycled to the process.

A main reaction and a side reaction take place in the reactor as follows:

Toluene + H2 Benzene + Methane

2Benzene diphenyl + hydrogen

19

Figure 2: HDA process flowsheet

20

CHAPTER THREE

METHODOLOGY

3.1 Unit-Based Control design methodology

In the past, unit-based control system design methodology has been widely used to

design PWC control systems. However, recent stringent environmental regulations,

safety concerns and economic considerations, demand design engineers to make

chemical processes highly integrated with material and/or energy recycles. Several

researchers (e.g., Luyben et al., 1998) studied the effect of these recycles on the

overall dynamics and concluded that these recycles need special attention while

designing PWC systems as they change the dynamics of the plant in a way which may

not always be apparent from the dynamics of the individual unit-operations. Hence,

because of the highly integrated nature of recent plants, unit-based methodology

seems to be scarcely equipped to design the control system for such complex plants.

This necessitates development of better methodologies which can deal with the highly

integrated processes in a more efficient way. This leads to the concept of PWC which

demands Plant-Wide perspective while designing PWC systems. This problem can be

best addressed by using simulation tools (i.e., process simulators) like ASPEN PLUS

(for steady state design) and ASPEN DYNAMICS (for control system design) that are

becoming increasingly popular and can give virtual hands-on experience to novices.

In addition, heuristics cannot always be totally relied upon as the solution can

sometimes be unconventional. Based on these, a simulation based heuristic

methodology that can handle PWC problems effectively and realistically would be

developed.

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3.2. SIMULATION OF HDA PROCESS

HDA process (Fig. 1) is a typical petrochemical process, extensively used by Douglas

(1988) to develop a conceptual design procedure. Designing control system for such a

process is really a challenging task because of the high level of interaction(due to

material and energy recycles) and three highly nonlinear (due to high purity

specifications) multi-component distillation columns. Steady-state simulation model

of HDA process was prepared using ASPEN PLUS, which was then exported to

ASPEN DYNAMICS that provides dynamic simulation capability. In this ASPEN

DYNAMICS environment, the dynamic model shares the same physical property

packages and flow-sheet topology as the steady-state model. However, there are

several differences in both these environments in terms of specifications given and

solution methodology. So, while moving from ASPEN PLUS TO ASPEN

DYNAMICS, a systematic procedure ,including plumbing, pressure-flow

specifications, equipment sizing was followed.

3.3. Plant-wide Control Design Objective

Step 1: set production rate

For this process, the essential is to produce pure benzene while minimizing yield

losses of hydrogen and diphenyl. The reactor effluent gas must be quenched to 1150

F. The design a control structures for process associate with energy integration can

be operated well.

Step 2. Determine Control Degree of Freedom.

There are 21 control degrees of freedom. They include: two fresh feed valves for

hydrogen and toluene, purge valve, separator base and overhead valves, cooler

22

cooling water valve, liquid quench valve, furnace fuel valve, stabilizer column steam;

reflux; cooling water; and vapor product valves, product column steam ; bottoms;

reflux; distillate; and cooling water valves, and recyclecolumn steam; bottoms;

reflux; and distillate.

Step 3. Establish Energy management system.

The reactor operates adiabatically, so for a given reactor design the exit temperature

depends upon the heat capacities of the reactor gases, reactor inlet temperature, and

reactor conversion. Heat from the adiabatic reactor is carried in the effluent stream

and is not removed from the process until it is dissipated to utility in the separator

cooler. Energy management of reaction section is handled by controlling the inlet and

exit streams temperature of the reactor. Reactor inlet temperature must be controlled

by adjusting fuel to the furnace and reactor exit temperature must be controlled by

quench to prevent the benzene yield decreases from the side reaction. In the reference

control structure, the effluent from the adiabatic reactor is quenched with liquid from

the separator. This quenched stream is the hot-side feed to the process-to-process heat

exchanger, where the cold stream is the reactor feed stream prior to the furnace. The

reactor effluent is then cooled with cooling water. The solutions to restore one degree

of freedom fairly easily have two ways. It is possible to oversize the P/P exchanger

and provides a controlled bypass around it. And it is possible to combine the P/P

exchanger with a utility exchanger.

Step 4. Set Production Rate.

Many control structures, there are not constrained to set production either by supply or

demand. Considering of the kinetics equation is found that the three variables alter the

reaction rate; pressure, temperature and toluene concentration(limiting agent).

Pressure is not a variable choice for production rate control because of the compressor

23

has to operate at maximum capacity for yield purposes. Reactor inlet temperature is

controlled by specify the reactant fresh feed rate and reactant composition into the

reactor constant. The reactor temperature is constrained below 1300 F for preventing

the cracking reaction that produce undesired by-product.

Toluene inventory can be controlled in two ways. Liquid level at the top of recycle

column is measured to change recycle toluene flow and total toluene feed flow in the

system is measured for control amount of fresh toluene feed flow. For on demand

control structure the production rate is set; distillate of product

column is flow control instead of level control so condenser level is controlled by

manipulating the total flow rate of the toluene.

24

Step 5. Control Product Quality and Handle Safety, Operational, and

Environmental Constraints.

Benzene quality can be affected primarily by two components, methane and toluene.

Any methane that leaves in the bottoms of the stabilizer column contaminates the

benzene product. The separation in the stabilizer column is used to prevent this

problem by using a temperature to set column stream rate (boilup). Toluene in the

overhead of the product column also affects benzene quality. Benzene purity can be

controlled by manipulating the column steam rate (boilup) to maintain temperature in

the column.

Step 6. Control Inventories and Fix a Flow in Every Recycle Loop.

In most processes a flow control should be present in all recycle loops. This is a

simple and effective way to prevent potentially large changes in recycle flows, while

the process is perturbed by small disturbance. We call this high sensitivity of the

recycle flowrates to small disturbances the snowball effect. Four pressures and

seven liquid levels must be controlled in this process. For the pressures, there are in

the gas loop and in the three distillation columns. In the gas loop, the separator

overhead valve is opened and run the compressor at maximum gas recycle rate to

improve yield so the gas loop control is related to the purge stream and fresh

hydrogen feed flow. In the stabilizer column, vapor product flow is used to

control pressure. In the product column, pressure control can be achieved by

manipulating cooling water flow, and in the product column pressure control can be

set by bypass valve of P/P heat exchanger to regulate overhead condensation rate. For

liquid control loops, there are a separator and two receivers in each column (base and

overhead). The most direct way to control separator level is with the liquid flow to

the stabilizer column. The stabilizer column overhead level is controlled with cooling

25

water flow and base level is controlled with bottom flow. In several cases of this

research; the product column, distillate flow controls overhead receiver level but on

demand control structure condenser level is controlled by cascade the total flow rate

of the toluene and bottom flow controls base level. In the recycle column manipulate

the total toluene flow to control level. The base level of recycle column in the

reference is controlled by manipulating the column steam flow because it has much

larger effect than bottoms flow. But the column steam flow does not obtain a good

controllability, so base level is controlled with bottom flow.

Step 7. Check Component Balances.

Component balances control loops consists of:

Methane is purged from the gas recycle loop to prevent it from accumulating and its

composition can be controlled with the purge flow. Diphenyl is removed in the bottom

stream from the recycle column, where bottom stream controls base level. And control

temperature (or concentration) with the reboiler steam. The inventory of benzene is

accounted for via temperature and overhead receiver level control in the product

column. But on demand structure the inventory of benzene is accounted for via

temperature and distillate flow control in the product column. Toluene inventory is

accounted for via level control in the recycle column overhead receiver. Gas loop

pressure control accounts for hydrogen inventory..

Step 8. Control Individual Unit Operations

The rest degrees of freedom are assigned for control loops within individual units.

These include:

Cooling water flow to the cooler controls process temperature to the separator;

Refluxs to the stabilizer, product, and recycle columns are flow controlled.

26

3.4. CONTROLLER DESIGN AND TUNING

Most of the controllers are easily tuned by simply using heuristics. All liquid levels

should use proportional only controllers with a gain of 2. All flow controllers should

use a gain of 0.5 and an integral time of 0.3 minutes (also enable filtering with a filter

time of 0.1 minutes). The default values in Aspen Dynamics for most pressure

controllers

seem to work reasonably well. Temperature controllers often need some adjustments.

The default transmitter ranges are usually too large, and spans should be set at about

10% of the absolute temperature level (typically a span of 100 K for moderate-

temperature processes). Distillation columns are typically controlled by manipulating

reboiler heat input to control the temperature on some selected tray. However, when

these heuristics dont give the needed convergence to steady state, process

identification would be used to obtain the transfer functions relating the manipulated

variables to the controlled variables, after which an IMC tuning rule would be used to

obtain the controllers parameters.

27

CHAPTER FOUR

STEADY-STATE AND DYNAMIC SIMULATION AND CONTROL

STRUCTURES PERFORMANCE EVALUATION

4.1. Steady-State Simulation

First, a steady-state model of the HDA process is built in ASPEN PLUS, using the

flow-sheet and equipment design information taken from luyben et al(1998). The data

and equipment specifications are given in the appendix section of this report. For this

simulation, peng-robinson model is selected for physical property calculations,

because of its reliability in predicting the properties of most hydrocarbon-based fluids

over a wide range of operating conditions. The reactor type used is a stoichiometric

reactor with a plug-flow dynamic model, because of non-availability of kinetic

parameters for a more suitable plug-flow reactor.

When columns are modelled in steady-state, besides the specifications of inlet

streams, pressure profiles, numbers of trays and feed trays, two specifications need to

be given for columns with reboiler and condenser. These could be the duties, reflux

rate, draw streams rate, composition fractions, etc. The detailed design data and

specifications for the columns are summarised in the appendix. Also, details of trays,

which are required for dynamic modelling are included. The simulated HDA process

at steady state in ASPEN PLUS is shown in figure 4.1 and 4.2 below. Note that figure

4.2 is a modified version of figure 4.1, with a bypass flow introduced around the

furnace and the FEHE.

28

Figure 4.1: Aspen Plus flow-sheet for HDA process

29

Figure 4.2: Aspen Plus flow-sheet for HDA process (with bybass)

30

4.2. Dynamic Simulation

The HDA dynamic simulation was done in ASPEN DYNAMICS. There are several

items that were taken into consideration in converting a steady-state simulation into a

dynamic simulation: all equipments were sized and control structures were

developed. Not all of the units that are available in steady-state ASPEN PLUS are

supported in ASPEN DYNAMICS, e.g. a DISTL type distillation column is not

supported in the dynamics, instead a rigorous RADFRAC model is used.

When the steady-state simulation in ASPEN PLUS is exported to ASPEN

DYNAMICS, a pressure-driven dynamic simulation is used to give a realistic

simulation. This requires that all the plumbing must be specified in the flow-sheet.

Pumps and compressors were inserted where needed to provide required pressure drop

for material flow. Control valves were installed where needed and their pressure drops

selected.

4.2.1. Equipment Sizing

For steady-state simulation, the size of the equipment is not needed, except for

reactors. For dynamic simulations, the inventories of material contained in all the

pieces of equipment affect the dynamic response, so the physical dimensions of all

units must be known.

In distillation columns, the diameter of the column, the weir height, and the sizes of

the reflux drum and the column base must be specified. Of course, before these can be

calculated, the number of stages and the feed stage location must be set by some

heuristics or rigorous optimization method. The easiest heuristic approach is to fix the

distillate and bottoms specifications ( using the Design Spec and Vary tools in Aspen

Plus) and keep increasing the number of stages until required reflux ratio stops

31

decreasing, this gives the minimum reflux ratio. Then, the actual reflux ratio is set at

1.2 times the minimum reflux ratio. Finally, the optimum feed stage can be

determined by varying the feed stage until the minimum reboiler energy is found. The

tray sizing section of the distillation column blocks in Aspen plus can be easily used

to provide the column diameter. The default weir height of 0.05m can be used. The

volumetric flow-rate of liquid into the reflux drum and the liquid into the base of the

column( the last stage or sump in Aspen terminology) can be used to size the two

vessels by using the heuristics of a 10-minutes hold-up time. These volumetric flow

rates are given in the hydraulic page tab of the profiles section of the column block.

Heat Exchanger tube-and-shell volumes can be calculated from the heat transfer areas,

which is known from the steady state design. Shell volume is approximately equal to

tube volume in most tube-and-shell heat exchanger.

4.2.2. Aspen Dynamics Environment and Plant-wide control structures

When the file containing the flow-sheet is opened in Aspen Dynamics, a default

control scheme is already installed on some loops. For example, level and pressure

controllers are inserted on all the distillation columns and reactors in the flow-sheet.

This default control scheme is modified and supplemented with other control loops to

incorporate a stable basic regulatory (decentralized) control structures. In this work,

two control structures are examined. The first is the reference control structure by

luyben et al (1998). In this control structure, the manipulated and controlled variables

are paired as given in table 4.1 below

32

Table 4.1: Pairing of controlled variables and manipulated variables

Controlled variables Manipulated variables

Gas recycle pressure Fresh feed hydrogen valves

Total toluene flow rate Fresh feed toluene valve

Reactor inlet temperature Furnace duty

Separator temperature Cooler duty

Quenched temperature Quench valve

Methane purge fraction Purge valve

Separator liquid level Stabiliser column feed valve

Stabiliser column reflux drum

level

Stabiliser col. condenser duty

Stabiliser column tray

temperature

Stabiliser col. reboiler duty

Stabiliser column pressure Stabiliser col. gas valve

Stabiliser column base level Product column feed valve

Product column reflux drum level Product col. Product valve

Product column base level Recycle col feed valve

Product col tray temperature Product col reboiler duty

Product col pressure Product col condenser duty

Recycle col reflux drum level Toluene recycle valve

Recycle col base level Recycle col reboiler duty

Recycle column temperature Recycle col bottom valve

Recycle column pressure Recycle column condenser duty

33

Figure 4.3: Aspen Dynamics flow-sheet for CS1

34

Figure 4.4: Aspen Dynamics Flow-sheet for CS2

35

The control structure II (CS2) adds a temperature control loop that controls furnace

inlet temperature by manipulating the bypass flow rate around the feed effluent heat

exchanger ( FEHE).

4.3. Control Structures Performance Evaluation

The two base-level regulatory control structures are tested using a rigorous non-linear

dynamic simulations of the entire system in ASPEN DYNAMICS. The effectiveness

of the control structures are checked using toluene recycle rate and reactor inlet

temperature changes as disturbances. These disturbances determine how the benzene

purity in the distillate stream from the product column is affected and also the

robustness of the control structure, i.e. how large a step disturbance we can make and

still have a stable response. Since the process is non-linear, performance is a function

of the forcing function.

The figures 4.5a & b, 4.6a & b and 4.7a & b below are the simulation results for step

change in disturbances ( reactor inlet temperature and toluene recycle flow-rate) for

CS1 and CS2. The results showed both the changing manipulated and the

corresponding controlled variables. Note that the disturbances were introduced after

10 minutes of simulation.

The results showed that the two control structures provide satisfactory disturbance

rejection in terms overshoot, settling time and stability. The reactor inlet temperature

change and the toluene recycle rate did not have an appreciable effect on the

production rate and purity of benzene. This showed that a good control structure with

an adequate tuning does well in the face of disturbances.

However, toluene recycle rate change did have an effect on the reactor inlet

temperature. In both CS1 and CS2, there is an undershoot(decrease) of less than 1%

36

change in the reactor inlet temperature and the responses settle back quickly to their

nominal value of 1200oF in about 50 minutes simulation time. Control Structure II

performs better in handling an increase in toluene recycle rate than control structure I.

Also, the response of the stabiliser column to reactor inlet temperature change was

oscillatory, gradually returning back to their nominal value in about 250 minutes of

simulation. The product column and recycle column temperature did not show an

appreciable change in their nominal values for both CS1 and CS2.

In general, a comparison of the control structures showed that CS2 has a faster

response and settling times than CS1 for the same sets of expected disturbances. This

might be due to introduction of bypass around the FEHE in CS2 which minimizes the

effect of the exchanger dynamics, thus providing a good control in the loops.

37

Time Minutes

que

nch

va

lve

0.0 50.0 100.0 150.0 200.0

75.0

125

.0

Time Minutes

Qu

enc

hT

em

p

0.0 50.0 100.0 150.0 200.0

115

0.0

115

5.0

116

0.0

Time Minutes

furn

ac

e d

uty

0.0 50.0 100.0 150.0 200.0

1.8

35

e+

007

1.8

55

e+

007

Time Minutes

reac

tor

inle

t te

mp

0.0 50.0 100.0 150.0 200.0

120

5.0

121

0.0

121

5.0

Time Minutes

fre

sh

to

lue

ne

fe

ed

va

lve

0.0 50.0 100.0 150.0 200.0

49.9

49.9

55

0.0

Time Minutes

TO

TT

OL

flo

wra

te lb

mol/

h

0.0 50.0 100.0 150.0 200.0

356

.85

356

.93

56

.95

Time Minutes

fre

sh

hyd

roge

n f

ee

d v

alv

e

0.0 50.0 100.0 150.0 200.0

49.8

49.9

50.0

Time Minutes

gas

re

cy

cle

pre

ss

ure

0.0 50.0 100.0 150.0 200.0

565

.55

66

.05

66

.55

67

.0

Figure 4.5a: Closed loop response of cs1 to 10oF increase in reactor inlet

temperature

38

Time Minutes

purg

e v

alv

e

0.0 50.0 100.0 150.0 200.0

50.0

50.0

01

Time Minutes

meth

ane

purg

e f

racti

on

0.0 50.0 100.0 150.0 200.0

0.6

54

42

50

.65

447

5

Time Minutes

coo

ler

du

ty

0.0 50.0 100.0 150.0 200.0

-2.4

9e

+0

07

-2.4

8e

+0

07

Time Minutes

sep

Te

mp

0.0 50.0 100.0 150.0 200.0

100

.01

00

.51

01

.01

01

.5

Time Minutes

sta

b.

col

feed

valv

e

0.0 50.0 100.0 150.0 200.0

50.0

51.0

Time Minutes

sep

Lev

el

0.0 50.0 100.0 150.0 200.0

5.5

5.6

Figure 4.5a: Closed loop response of cs1 to 10oF increase in reactor inlet

temperature(contd)

39

Time Minutes

sta

b.

col.

re

bo

iler

du

ty

0.0 50.0 100.0 150.0 200.0

3.5

11

e+

006

3.5

12

e+

006

Time Minutes

Sta

b.C

ol.

Te

mp

0.0 50.0 100.0 150.0 200.0 250.0

336

.14

336

.16

Time Minutes

sta

b.

col.

ga

s v

alv

e

0.0 50.0 100.0 150.0 200.0

49.0

50.0

51.0

52.0

Time Minutes

Sta

b.C

ol.

Pre

ss

0.0 50.0 100.0 150.0 200.0

108

.97

Time Minutes

pro

du

ct

co

l re

bo

iler

du

ty

0.0 50.0 100.0 150.0 200.0

7.1

29

e+

00

67

.13

05e

+0

06

Time Minutes

Pro

du

ctC

olT

em

p

0.0 50.0 100.0 150.0 200.0

238

.4

Time Minutes

pro

du

ct

co

lun

co

nde

nse

r

0.0 50.0 100.0 150.0 200.0

-8.3

1e

+0

06

-8.3

e+

00

6

Time Minutes

Pro

dC

olP

ress

.

0.0 50.0 100.0 150.0 200.0

19.9

Figure 4.5a: Closed loop response of cs1 to 10oF increase in reactor inlet

temperature (contd)

40

Time Minutes

recy

cle

colu

mn

bott

om

va

lve

0.0 50.0 100.0 150.0 200.0

49.0

50.0

51.0

Time Minutes

Re

cyC

olT

em

p

0.0 50.0 100.0 150.0 200.0

317

.7

Time Minutes

recy

cle

col

con

den

ser

du

ty

0.0 50.0 100.0 150.0 200.0

-1.5

5e

+0

06

-1.5

e+

00

6

Time Minutes

Re

cyC

olP

ress

0.0 50.0 100.0 150.0 200.0

20.1

Time Minutes

ben

zen

e p

urity

0.0 50.0 100.0 150.0 200.0

0.9

0.9

51.0

1.0

51.1

Time Minutes

ben

zen

e f

low

rate

,lbm

ol/h

0.0 50.0 100.0 150.0 200.0

255

.0260

.0

Figure 4.5a: Closed loop response of cs1 to 10oF increase in reactor inlet

temperature (contd)

41

Time Minutes

furn

ac

e d

uty

0.0 50.0 100.0 150.0

1.8

19

e+

007

Time Minutes

reac

tor

inle

t te

mp

0.0 50.0 100.0 150.0

119

9.0

120

0.0

Time Minutes

que

nch

va

lve

0.0 50.0 100.0 150.0 200.0

300

.06

00

.0

Time Minutes

Qu

enc

hT

em

p

0.0 50.0 100.0 150.0

114

8.0

114

9.0

Time Minutes

fre

sh

to

lue

ne

fe

ed

va

lve

0.0 50.0 100.0 150.0

50.0

15

0.0

2

Time Minutes

TO

TT

OL

flo

wra

te lb

mol/

h

0.0 50.0 100.0 150.0

356

.83

356

.84

Time Minutes

fre

sh

hyd

roge

n f

ee

d v

alv

e

0.0 50.0 100.0 150.0

50.0

35

0.0

8

Time Minutes

gas

re

cy

cle

pre

ss

ure

0.0 50.0 100.0 150.0

564

.95

65

.05

65

.15

65

.2

Figure 4.5b: closed loop response of cs1 to 2oF decrease in reactor inlet

Temperature

42

Time Minutes

purg

e v

alv

e

0.0 50.0 100.0 150.0

48.0

49.0

50.0

51.0

52.0

Time Minutes

meth

ane

purg

e f

racti

on

0.0 50.0 100.0 150.0

0.6

54

50

.65

5

Time Minutes

coo

ler

du

ty

0.0 50.0 100.0 150.0

-2.4

71

e+

007

Time Minutes

sep

Te

mp

0.0 50.0 100.0 150.0

99.8

Time Minutes

sta

b.

col

feed

valv

e

0.0 50.0 100.0 150.0 200.0

50.0

51.0

Time Minutes

sep

Lev

el

0.0 50.0 100.0 150.0

5.6

Figure 4.5b: closed loop response of cs1 to 2oF decrease in reactor inlet

Temperature(contd)

43

Time Minutes

sta

bili

ser

co

l re

boiler

du

ty

0.0 50.0 100.0 150.0 200.0

3.5

e+

00

63

.6e

+00

6

Time Minutes

Sta

b.C

ol.

Te

mp

0.0 50.0 100.0 150.0

336

.132

336

.137

Time Minutes

sta

b.

col.

ga

s v

alv

e

0.0 50.0 100.0 150.0 200.0

49.0

50.0

51.0

Time Minutes

Sta

b.C

ol.

Pre

ss

0.0 50.0 100.0 150.0

109

.01

10

.0

Time Minutes

pro

du

ct

co

l re

bo

iler

du

ty

0.0 50.0 100.0 150.0

7.1

30

5e

+0

06

Time Minutes

Pro

du

ctC

olT

em

p

0.0 50.0 100.0 150.0

238

.4

Figure 4.5b: closed loop response of cs1 to 2oF decrease in reactor inlet

Temperature(contd)

44

Time Minutes

pro

du

ct

co

l c

ond

ens

er

du

ty

0.0 50.0 100.0 150.0 200.0

-8.4

e+

00

6-8

.3e

+00

6-8

.2e

+00

6

Time Minutes

Pro

dC

olP

ress

.

0.0 50.0 100.0 150.0

19.9

Time Minutes

recy

cle

colu

mn

bott

om

va

lve

0.0 50.0 100.0 150.0 200.0

49.0

50.0

51.0

Time Minutes

Re

cyC

olT

em

p

0.0 50.0 100.0 150.0

317

.7

Time Minutes

recy

cle

col

con

den

ser

du

ty

0.0 50.0 100.0 150.0 200.0

-1.5

e+

00

6-1

.4e

+00

6

Time Minutes

Re

cyC

olP

ress

0.0 50.0 100.0 150.0

20.1

Figure 4.5b: closed loop response of cs1 to 2oF decrease in reactor inlet

Temperature(contd)

45

Time Minutes

fre

sh

hyd

roge

n f

eed

valv

e

0.0 50.0 100.0 150.0 200.0

49.8

49.9

50.0

Time Minutes

gas

re

cy

cle

pre

ssu

re

0.0 50.0 100.0 150.0 200.0

565

.75

566

.25

Time Minutes

fre

sh

fe

ed

to

l v

ave

0.0 50.0 100.0 150.0 200.0

45.0

60.0

Time Minutes

tott

ol

flow

rate

lb

mo

l/h

0.0 50.0 100.0 150.0 200.0

356

.885

356

.91

Time Minutes

purg

e v

alv

e

0.0 50.0 100.0 150.0 200.0

45.0

50.0

55.0

Time Minutes

meth

ane

purg

e f

rac

tio

n

0.0 50.0 100.0 150.0 200.0

0.6

54

50

.65

5

Figure 4.6a: closed loop response of cs2 to 10oF increase in reactor inlet

temperature

46

Time Minutes

furn

ac

e d

uty

0.0 40.0 80.0 120.0 160.0 200.0

2.1

3e

+0

072.1

4e

+0

072

.15

e+0

07

Time Minutes

reac

tor

inle

t te

mp

.

0.0 50.0 100.0 150.0 200.0

120

4.0

120

8.0

121

2.0

Time Minutes

byb

ass

valv

e

0.0 50.0 100.0 150.0 200.0

60.0

70.0

80.0

90.0

100

.0

Time Minutes

furn

ac

e i

nle

t te

mp.

0.0 50.0 100.0 150.0 200.0

967

.59

72

.59

77

.5

Time Minutes

que

nch

valv

e

0.0 50.0 100.0 150.0 200.0

60.0

70.0

80.0

90.0

100

.0

Time Minutes

que

nch

te

mp

0.0 50.0 100.0 150.0 200.0

115

0.0

115

5.0

116

0.0

Figure 4.6a: closed loop response of cs2 to 10oF increase in reactor inlet

temperature(contd)

47

Time Minutes

coo

ler

du

ty

0.0 50.0 100.0 150.0 200.0

-2.8

e+

00

7-2.7

9e

+0

07

-2.7

8e

+0

07

Time Minutes

sep

.Te

mp

0.0 50.0 100.0 150.0 200.0

100

.05

100

.3

Time Minutes

sta

b c

ol

feed

valv

e

0.0 50.0 100.0 150.0 200.0

49.0

50.0

51.0

52.0

Time Minutes

sep

.Lev

el

0.0 50.0 100.0 150.0 200.0

5.4

85

.49

5.5

Time Minutes

sta

b c

ol

rebo

iler

du

ty

0.0 50.0 100.0 150.0 200.0

3.5

1e

+0

06

3.5

2e

+0

06

Time Minutes

sta

bili

ser

co

l. t

em

p

0.0 50.0 100.0 150.0 200.0 250.0

336

.15

336

.2

Figure 4.6a: closed loop response of cs2 to 10oF increase in reactor inlet

temperature(contd)

48

Time Minutes

sta

b c

ol

gas

valv

e

0.0 50.0 100.0 150.0 200.0

50.0

52.5

Time Minutes

sta

bili

ser

co

l. p

res

su

re

0.0 50.0 100.0 150.0 200.0

109

.0

Time Minutes

pro

du

ct

co

l re

boiler

duty

0.0 50.0 100.0 150.0 200.0

7.1

3e

+0

06

7.1

31

e+

006

Time Minutes

pro

du

ct

co

lum

n t

em

p

0.0 50.0 100.0 150.0 200.0238

.02

238

.22

38

.38

Time Minutes

pro

du

ct

co

l c

ond

en

ser

du

ty

0.0 50.0 100.0 150.0 200.0

-8.3

17

e+

006-

8.3

16

e+

006

Time Minutes

pro

du

ct

co

l. p

ress

ure

0.0 50.0 100.0 150.0 200.0

20.0

Figure 4.6a: closed loop response of cs2 to 10oF increase in reactor inlet

temperature(contd)

49

Time Minutes

recy

cle

col

con

den

ser

du

ty

0.0 50.0 100.0 150.0 200.0-1.5

34

95

e+0

06-1

.53

48e

+00

6

Time Minutes

recy

cle

col

pre

ss

ure

0.0 50.0 100.0 150.0 200.0

19.0

20.0

21.0

Time Minutes

recy

cle

col

bott

om

va

lve

0.0 50.0 100.0 150.0 200.0

49.0

50.0

51.0

52.0

Time Minutes

recy

cle

co

l te

mp

0.0 50.0 100.0 150.0 200.0

318

.0

Time Minutes

ben

zen

e f

low

rate

0.0 50.0 100.0 150.0 200.0

255

.0260

.0

Time Minutes

ben

zen

e p

urity

0.0 50.0 100.0 150.0 200.0

0.9

0.9

51.0

1.0

51.1

Figure 4.6a: closed loop response of cs2 to 10oF increase in reactor inlet

temperature(contd)

50

Time Minutes

fre

sh

fe

ed h

ydro

gen

valv

e

0.0 50.0 100.0 150.0 200.0

49.0

84

9.3

84

9.6

84

9.9

8

Time Minutes

gas

re

cy

cle

pre

ss

ure

0.0 50.0 100.0 150.0 200.0

565

.05

65

.55

66

.0

Time Minutes

fre

sh

fe

ed

to

l v

ave

0.0 50.0 100.0 150.0 200.0

60.0

Time Minutes

tota

l to

lue

ne

flo

wra

te

0.0 50.0 100.0 150.0 200.0

356

.85

356

.9

Time Minutes

purg

e v

alv

e

0.0 50.0 100.0 150.0 200.0

50.0

55.0

Time Minutes

meth

ane

purg

e f

rac

tion

0.0 50.0 100.0 150.0 200.0

0.6

54

5

Time Minutes

furn

ac

e d

uty

0.0 50.0 100.0 150.0 200.0

2.1

2e

+0

072

.16

e+0

072

.2e

+00

7

Time Minutes

reac

tor

inle

t te

mpe

ratu

re

0.0 40.0 80.0 120.0 160.0 200.0

119

8.0

119

9.0

120

0.0

120

1.0

Figure 4.6b: closed loop response of cs2 to 2oF decrease in reactor inlet

temperature

51

Time Minutes

byp

ass

valv

e

0.0 50.0 100.0 150.0 200.0

100

.0

Time Minutes

furn

ac

e i

nle

t te

mpe

ratu

re

0.0 50.0 100.0 150.0 200.0

962

.09

64

.09

66

.09

68

.0

Time Minutes

que

nch

valv

e

0.0 50.0 100.0 150.0 200.0

100

.0

Time Minutes

que

nch

te

mp

0.0 50.0 100.0 150.0 200.0

114

6.0

114

8.0

115

0.0

Time Minutes

coo

ler

du

ty

0.0 50.0 100.0 150.0 200.0

-2.7

79

e+

007

Time Minutes

Se

pT

em

p

0.0 50.0 100.0 150.0 200.0

99.8

99.8

59

9.9

Time Minutes

sta

b c

ol

feed

valv

e

0.0 50.0 100.0 150.0 200.0

48.5

49.0

49.5

50.0

50.5

51.0

Time Minutes

sep

lev

el

0.0 50.0 100.0 150.0 200.0

5.4

75

.48

5.4

95

.5

Figure 4.6b: closed loop response of cs2 to 2oF decrease in reactor inlet

temperature(contd)

52

Time Minutes

sta

b c

ol

gas

valv

e

0.0 50.0 100.0 150.0 200.0

50.0

52.5

Time Minutes

sta

bili

ser

co

l p

res

sure

0.0 50.0 100.0 150.0 200.0

108

.95

109

.0

Time Minutes

sta

b c

ol

rebo

iler

du

ty

0.0 50.0 100.0 150.0 200.0

3.5

11

e+

006

Time Minutes

sta

bili

ser

tem

p

0.0 50.0 100.0 150.0 200.0

336

.15

336

.2

Time Minutes

pro

du

ct

co

l re

boiler

duty

0.0 50.0 100.0 150.0 200.0

7.1

30

5e

+00

6

Time Minutes

pro

du

ct

co

l te

mp

0.0 50.0 100.0 150.0 200.0

238

.52

39

.0

Figure 4.6b: closed loop response of cs2 to 2oF decrease in reactor inlet

temperature(contd)

53

Time Minutes

pro

du

ct

co

l c

ond

en

ser

du

ty

0.0 50.0 100.0 150.0 200.0

-8.3

17

1e

+00

6-8

.31

69e

+00

6

Time Minutes

pro

du

ct

co

l pre

ssu

re

0.0 50.0 100.0 150.0 200.0

19.8

651

19.8

652

Time Minutes

recy

cle

col

con

den

ser

du

ty

0.0 50.0 100.0 150.0 200.0

-1.5

3e

+0

06

-1.5

2e

+0

06

Time Minutes

recy

cle

co

l p

ress

ure

0.0 50.0 100.0 150.0 200.0

19.0

20.0

21.0

22.0

Time Minutes

recy

cle

col

bott

om

va

lve

0.0 50.0 100.0 150.0 200.0

49.5

50.0

50.5

51.0

Time Minutes

recy

cle

col

tem

p

0.0 50.0 100.0 150.0 200.0

317

.23

17

.63

18

.0

Time Minutes

ben

zen

e f

low

rate

0.0 50.0 100.0 150.0 200.0

255

.0260

.0

Time Minutes

ben

zen

e p

urity

0.0 50.0 100.0 150.0 200.0

0.9

0.9

51.0

1.0

51.1

Figure 4.6b: closed loop response of cs2 to 2oF decrease in reactor inlet

temperature(contd)

54

Time Minutes

fre

sh

fe

ed

hyd

roge

n v

alv

e

0.0 50.0 100.0 150.0 200.0

60.0

80.0

Time Minutes

gas

re

cy

cle

pre

ss

ure

0.0 50.0 100.0 150.0 200.0

565

.25

565

.55

65

.75

Time Minutes

fre

sh

fe

ed

to

l v

alv

e

0.0 50.0 100.0 150.0 200.0

50.0

100

.0

Time Minutes

TO

TO

L,l

bm

ol/

hr

0.0 50.0 100.0 150.0 200.0

357

.05

357

.3

Time Minutes

purg

e v

alv

e

0.0 50.0 100.0 150.0

49.0

50.0

51.0

Time Minutes

meth

ane

purg

e f

rac

tn

0.0 50.0 100.0 150.0 200.0

0.6

54

50

.65

50

.65

55

Figure 4.7a: closed loop response of cs1 to 47 lb/h increase in recycle toluene

flowrate

55

Time Minutes

coo

ler

du

ty

0.0 25.0 50.0 75.0 100.0 125.0 150.0

-2.4

76

5e

+00

7-2

.47

5e+

007

Time Minutes

sep

Te

mp

0.0 50.0 100.0 150.0 200.0

99.6

59

9.9

Time Minutes

furn

ac

e d

uty

0.0 50.0 100.0 150.0

1.8

2e

+0

07

1.8

21

e+

007

Time Minutes

reac

tor

inle

t te

mp

0.0 50.0 100.0 150.0 200.0

119

9.0

120

0.0

120

1.0

Time Minutes

que

nch

va

lve

0.0 50.0 100.0 150.0 200.0

100

.02

00

.03

00

.0

Time Minutes

que

nch

tem

p

0.0 50.0 100.0 150.0 200.0

114

9.4

51

14

9.7

Figure 4.7a: closed loop response of cs1 to 47 lb/h increase in recycle toluene

flowrate(contd)

56

Time Minutes

sta

b.

col.

ga

s v

alv

e

0.0 50.0 100.0 150.0 200.0

48.0

51.0

54.0

Time Minutes

sta

bili

ser

co

l p

res

sure

0.0 50.0 100.0 150.0 200.0

107

.01

08

.01

09

.01

10

.0

Time Minutes

sta

bili

ser

co

l re

boiler

du

ty

0.0 50.0 100.0 150.0 200.0

3.5

e+

00

63

.55

e+0

06

Time Minutes

sta

bili

ser

co

l te

mp.

0.0 50.0 100.0 150.0 200.0

335

.53

36

.03

36

.53

37

.0

Time Minutes

pro

du

ct

co

l re

bo

iler

du

ty

0.0 50.0 100.0 150.0 200.0

7.1

3e

+0

067.1

35

e+

00

67.1

4e

+0

06

Time Minutes

Pro

du

ctC

olT

em

p

0.0 50.0 100.0 150.0 200.0

237

.52

38

.02

38

.52

39

.0

Figure 4.7a: closed loop response of cs1 to 47 lb/h increase in recycle toluene

flowrate(contd)

57

Time Minutes

pro

du

ct

co

l c

ond

ens

er

du

ty

0.0 50.0 100.0 150.0 200.0

-8.3

4e

+0

06

-8.3

2e

+0

06

-8.3

e+

00

6

Time Minutes

Pro

du

ctC

olP

res

su

re

0.0 50.0 100.0 150.0 200.0

19.7

51

9.8

19.8

51

9.9

Time Minutes

recy

cle

col

bott

om

va

lve

0.0 50.0 100.0 150.0 200.0

48.5

49.0

49.5

50.0

50.5

Time Minutes

recy

cle

col

tem

p

0.0 50.0 100.0 150.0 200.0

317

.03

18

.03

19

.03

20

.0

Time Minutes

recy

cle

col

con

den

ser

du

ty

0.0 50.0 100.0 150.0 200.0

-1.5

4e

+0

06

-1.5

3e

+0

06

Time Minutes

recy

cle

col

pre

ss

ure

0.0 50.0 100.0 150.0 200.0

19.5

20.0

20.5

21.0

Figure 4.7a: closed loop response of cs1 to 47 lb/h increase in recycle toluene

flowrate(contd)

58

Time Minutes

fre

sh

fe

ed h

ydro

gen

valv

e

0.0 50.0 100.0 150.0 200.0

24.0

32.0

40.0

48.0

56.0

Time Minutes

gas

re

cy

cle

pre

ssu

re

0.0 50.0 100.0 150.0 200.0

565

.55

66

.05

66

.5

Time Minutes

fre

sh

fe

ed

to

l v

ave

0.0 50.0 100.0 150.0 200.0

70.0

140

.0

Time Minutes

TO

TO

L,l

b/m

ol

0.0 50.0 100.0 150.0 200.0

357

.25

357

.75

Time Minutes

purg

e v

alv

e

0.0 50.0 100.0 150.0 200.0

50.0

55.0

Time Minutes

meth

ane

pu

rge

fra

ctn

0.0 50.0 100.0 150.0 200.0

0.6

55

0.6

56

Time Minutes

furn

ac

e d

uty

0.0 40.0 80.0 120.0 160.0 200.0

2.1

29

5e

+0

07

2.1

31

5e

+0

07

Time Minutes

reac

tor

inle

t te

mp.

0.0 50.0 100.0 150.0 200.0

120

0.0

120

1.0

Figure 4.7b: closed loop response of cs2 to 82 lb/hr increase in recycle toluene

rate

59

Time Minutes

byp

ass

valv

e

0.0 50.0 100.0 150.0 200.0

46.0

48.0

50.0

52.0

54.0

56.0

Time Minutes

furn

ac

e i

nle

t te

mp

0.0 50.0 100.0 150.0 200.0

964

.65

964

.9

Time Minutes

que

nch

va

lve

0.0 50.0 100.0 150.0 200.0

50.0

100

.0

Time Minutes

que

nch

te

mp

0.0 50.0 100.0 150.0 200.0

114

9.4

114

9.6

114

9.8

Time Minutes

coo

ler

du

ty

0.0 50.0 100.0 150.0 200.0

-2.7

84

e+

007

Time Minutes

Se

pT

em

p

0.0 50.0 100.0 150.0 200.0

99.9

99.9

51

00

.0

Time Minutes

sta

b c

ol

rebo

iler

du

ty

0.0 50.0 100.0 150.0 200.0

3.5

e+

00

63

.52

e+0

06

Time Minutes

sta

bili

ser

co

l te

mp

0.0 50.0 100.0 150.0

335

.53

36

.03

36

.53

37

.0

Figure 4.7b: closed loop response of cs2 to 82 lb/hr increase in recycle toluene

rate (contd)

60

Time Minutes

sta

b c

ol

gas

valv

e

0.0 50.0 100.0 150.0 200.0

45.0

50.0

55.0

Time Minutes

sta

b c

ol p

ress

ure

0.0 50.0 100.0 150.0

108

.95

109

.0

Time Minutes

pro

du

ct

co

l c

ond

en

ser

du

ty

0.0 50.0 100.0 150.0 200.0

-8.3

e+

00

6-8

.2e

+00

6

Time Minutes

pro

du

ct

co

l p

ress

ure

0.0 50.0 100.0 150.0 200.0

19.8

65

19.8

7

Time Minutes

pro

du

ct

co

l re

boiler

duty

0.0 50.0 100.0 150.0 200.0

7.1

3e

+0

06

Time Minutes

pro

du

ct

co

l te

mp

0.0 50.0 100.0 150.0 200.0

238

.31

238

.34

238

.37

238

.4

Time Minutes

recy

cle

col

bott

om

va

lve

0.0 50.0 100.0 150.0 200.0

50.0

50.5

51.0

Time Minutes

recy

cle

col

tem

p

0.0 50.0 100.0 150.0 200.0

318

.0

Figure 4.7b: closed loop response of cs2 to 82 lb/hr increase in recycle toluene

rate (contd)

61

Time Minutes

recy

cle

col

con

den

ser

du

ty

0.0 50.0 100.0 150.0 200.0

-1.5

35

e+

006

-1.5

3e

+0

06

Time Minutes

recy

cle

col

pre

ss

ure

0.0 50.0 100.0 150.0 200.0

19.0

20.0

21.0

Time Minutes

recy

cle

tolu

ene

flo

w, lb

/h

0.0 50.0 100.0 150.0 200.0

810

0.0

820

0.0

830

0.0

840

0.0

Time Minutes

ben

zen

e p

urity

0.0 50.0 100.0 150.0 200.0

0.9

0.9

51.0

1.0

51.1

Figure 4.7b: closed loop response of cs2 to 82 lb/hr increase in recycle toluene

rate (contd)

Time Minutes

ben

zen

e p

rod r

ate

0.0 50.0 100.0 150.0 200.0

250

.0260

.0270

.0

62

CHAPTER FIVE

CONCLUSION AND RECOMMENDATION

5.1 Conclusion

Most industrial processes contain a complex flow-sheet with several recycle streams,

energy integration, and many different unit operations. The economic can be

improved by introducing recycle streams and energy integration into the process.

However, the recycle streams and energy integration introduce a feedback of material

and energy among units upstream and downstream. Therefore, strategies for plant-

wide control are required to operate an entire plant safely and achieve its design

objectives. Hydrodealkylation (HDA) process of toluene to benzene consists of a

reactor, furnace, vapour-liquid separator, recycle compressor, heat exchangers and

distillations. This plant is a realistic complex chemical process. It is considering that

the energy integration for realistic and large processes is meaningful and useful, it is

essential to design a control strategy for process associated with energy integration, so

it can be operated well. For HDA process control structures developed, the effects of

disturbances could be reduced in order to keep the production rate as desired value.

This work presents two plant-wide designed control structures. The dynamic

simulation of this process with various disturbances is made to evaluate performance

of each control structures: increasing and decreasing the reactor inlet temperature,

increasing the recycle toluene rate. Control Structure II (CS2) was found to be more

robust and stabilises quickly than control structure I (CS1).

The result shows that the dynamic performance of hydrodealkylation of toluene

process deteriorates when the process incorporates complex heat integration.

63

5.1 Recommendations

From the simulation results, it would be observed that the control objective of

maintaining the quench temperature at 1150oF was not realised. This is due mainly to

the non-availability of kinetic parameters which made the use of plug flow reactor

impossible. I would therefore recommend that a plug flow reactor should be used for

future work on this process. Also, the use of MPC plant-wide control of HDA process

should be studied as well.

64

REFERENCES

Downs, J.J. and Vogel, E.F. A plant-wide Industrial process control problem.

Computer and Chem. Eng. 17, 3 ( 1993): 245-255.

Luyben, M.L, Tyreus, B.D, and Luyben, W.L. plant-wide process control.

Newyork, McGraw-Hill, 1999.

Mcavoy, T. Synthesis of plant-wide control systems using optimisation. Ind. Eng.

Chem. Res. 38(1999): 2984-2994.

Price, R.M, Lyman, P.R and Georgakis, C Throughput manipulation in plant-wide

Control structures. Ind. Eng. Chem. Res 33(1994) : 1197-1207.

Skogestad, S, and Larsson, T.A. review of plant-wide control. Department of

Chemical Engineering. Norwegian University of Science and

Technology. (1998): 1-33.

65

APPENDIX A

Table A1: Data of HDA process for simulation

HDA process

Stream ID 1 2 3 4 5 6 7 8 9 10 11

From B15 HX1 H1 B12 M2 HX1 H2 P1 F1 S2 S2

To H1 B15 R1 B7 HX1 H2 F1 B3 S2 P1 B4

Phase VAPOR VAPOR VAPOR LIQUID VAPOR VAPOR MIXED LIQUID LIQUID LIQUID LIQUID

Subst ream: MIXED

Mole Flow lbmol/hr

HYDROGEN 2096.964 2003.580 2096.964 2.0652E-12 1832.982 1832.982 1832.982 .6146751 1.735390 .6146751 1.120705

METHANE 3306.586 3159.334 3306.586 3.87338E-7 3584.726 3584.726 3584.726 10.38456 29.31835 10.38456 18.93389

BENZENE 48.11924 45.97634 48.11924 257.0477 457.5263 457.5263 457.5263 147.9689 417.7551 147.9689 269.7863

TOLUENE 357.0076 341.1090 357.0076 5.894240 135.9823 135.9823 135.9823 46.73035 131.9321 46.73035 85.20170

BIPHENYL 1.40408E-3 1.34155E-3 1.40408E-3 1.2172E-26 4.893188 4.893188 4.893188 1.733034 4.892811 1.733034 3.159785

WATER 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

Mole Frac

HYDROGEN .3610054 .3610054 .3610054 7.8543E-15 .3046789 .3046789 .3046789 2.96327E-3 2.96327E-3 2.96327E-3 2.96324E-3

METHANE .5692493 .5692493 .5692493 1.47309E-9 .5958545 .5958545 .5958545 .0500626 .0500626 .0500626 .0500628

BENZENE 8.28403E-3 8.28403E-3 8.28403E-3 .9775835 .0760502 .0760502 .0760502 .7133385 .7133385 .7133385 .7133385

TOLUENE .0614610 .0614610 .0614610 .0224165 .0226030 .0226030 .0226030 .2252809 .2252809 .2252809 .2252807

BIPHENYL 2.41722E-7 2.41722E-7 2.41722E-7 4.6292E-29 8.13348E-4 8.13348E-4 8.13348E-4 8.35473E-3 8.35473E-3 8.35473E-3 8.35475E-3

WATER 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

Total Flow lbmol/hr 5808.678 5550.000 5808.678 262.9419 6016.109 6016.109 6016.109 207.4315 585.6337 207.4315 378.2024

Total Flow lb/hr 93927.84 89744.96 93927.84 20622.03 1.10227E+5 1.10227E+5 1.10227E+5 16299.23 46017.04 16299.23 29717.80

Total Flow cuft/hr 1.60264E+5 1.56893E+5 2.12758E+5 412.0844 2.13679E+5 1.14890E+5 67963.49 311.1514 878.3536 311.1129 567.2408

Temperature F 964.8277 1000.000 1200.000 196.6682 1149.461 404.9529 100.0000 100.1882 100.0000 100.0000 100.0000

Pressure psia 562.0000 562.0000 492.0000 20.00000 492.0000 487.0000 482.0000 494.0000 482.0000 482.0000 482.0000

Vapor Frac 1.000000 1.000000 1.000000 0.0 1.000000 1.000000 .9026557 0.0 0.0 0.0 0.0

Liquid Frac 0.0 0.0 0.0 1.000000 0.0 0.0 .0973442 1.000000 1.000000 1.000000 1.000000

Solid Frac 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

Enthalpy Btu/lbmol -5858.539 -5328.295 -2195.808 24730.18 -1454.949 -12439.23 -17065.47 15862.74 15854.45 15854.45 15854.44

Enthalpy Btu/lb -362.3033 -329.5120 -135.7930 315.3231 -79.41002 -678.9234 -931.4200 201.8764 201.7709 201.7709 201.7708

Enthalpy Btu/hr -3.4030E+7 -2.9572E+7 -1.2755E+7 6.50260E+6 -8.7531E+6 -7.4836E+7 -1.0267E+8 3.29043E+6 9.28490E+6 3.28871E+6 5.99619E+6

Ent ropy Btu/lbmol-R -8.936848 -8.569146 -6.291718 -53.92081 -6.840387 -15.83146 -22.48581 -61.14008 -61.14836 -61.14836 -61.14835

Ent ropy Btu/lb-R -.5526718 -.5299324 -.3890919 -.6875192 -.3733431 -.8640689 -1.227258 -.7780964 -.7782018 -.7782018 -.7782018

Density lbmol/cuft .0362445 .0353744 .0273018 .6380778 .0281549 .0523642 .0885197 .6666578 .6667403 .6667403 .6667404

Density lb/cuft .5860834 .5720134 .4414777 50.04321 .5158536 .9594167 1.621857 52.38362 52.39010 52.39010 52.39010

Average MW 16.17026 16.17026 16.17026 78.42807 18.32199 18.32199 18.32199 78.57648 78.57648 78.57648 78.57646

Liq Vol 60F cuft/hr 5309.720 5073.262 5309.720 374.4374 5539.509 5539.509 5539.509 302.8290 854.9661 302.8290 552.1372

*** ALL PHASES ***

QVALGRS Btu/lb 23331.64 23331.64 23331.64 17993.20 22524.62 22524.62 22524.62 18118.53 18118.53 18118.53 18118.54

66

Table A1: Data of HDA process for simulation(contd)

HDA process

Stream ID H2-FEED TOL-FEED GAS-RECY TOL-RECY PURGE 12 13 14 15 16 17

From C1 P2 S1 B14 B1 B13 B16 F1 S1

To B1 B2 M1 B10 B14 M1 B9 B15 S1 C1

Phase VAPOR LIQUID VAPOR LIQUID VAPOR VAPOR VAPOR LIQUID MIXED VAPOR VAPOR

Substream: MIXED

Mole Flow lbmol/hr

HYDROGEN 393.9000 0.0 1703.064 0.0 128.1872 128.1872 393.9000 0.0 93.38402 1831.246 1703.059

METHANE 0.0 0.0 3306.586 0.0 248.8785 248.8785 0.0 0.0 147.2521 3555.407 3306.529

BENZENE 0.0 0.0 36.98775 11.13148 2.783986 2.783986 0.0 6.54181E-4 2.142892 39.77122 36.98724

TOLUENE 0.0 274.2000 3.766705 79.04093 .2835116 .2835116 0.0 .2566318 15.89861 4.05016