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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.
21
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