16 14 Advance control in a Debutanizer PDVSA · PDF file2 ADVANCED CONTROL STRATEGY DESIGN TO MINIMIZE DISTURBING EFFECTS ON PRODUCT QUALITY IN A DEBUTANIZER FRACTIONATION COLUMN Gerencia

Gerencia de Procesamiento de Gas Occidente

ADVANCED CONTROL STRATEGY DESIGN TO MINIMIZE DISTURBING EFFECTS ON PRODUCT QUALITY IN A DEBUTANIZER FRACTIONATION COLUMN

AÑO

2010

Authors: Msc. Keyla Guerra Bracho

Msc. Roberto Paz

Management: Procesamiento de Gas

2 ADVANCED CONTROL STRATEGY DESIGN TO MINIMIZE DISTURBING EFFECTS ON PRODUCT QUALITY IN A DEBUTANIZER FRACTIONATION COLUMN


ABSTRACT

The objective of this research was to design an advanced control strategy that would allow quality control of products from top and bottom of the debutanizer tower V‐303 of the Bajo Grande Fractionation Plant. Disturbance variables are flow and temperature in the tower feedstock, considering the new characterization of NGL from Western Cryogenic Complex CCO. The new composition of feedgas will enter Bajo Grande plant once it is released to service the complex. The process of collecting data was obtained through the simulation software Hysys Version 3.2 in a steady‐state calculation to determine the characterization of the feedgas and dynamic‐state simulation because the CCO is currently in engineering phase. The disturbance variables were realized in stepwise open loop and with data obtained system identification was achieved in matlab version 7.0. After analysis of stability control systems, transfers equations in “la place” domain were calculated. Some strategies designed in advanced control block diagram and represented in the Matlab Simulink software enabled a comparison of responses obtained from a PI control, cascade control and Feedfoward up with the flow and temperature disturbances at the entrance and stood references setpoints in top or bottom, was selected as the feedfoward control as the advanced control strategy that produced better and faster response from disturbances analyzed and kept in temperature controls for top and bottom within the quality parameters of the butanes and natural gasoline that is required.



INTRODUCTION

PDVSA GAS encompassing increasing production projects and social

development policy with socialist vision is supporting in western Venezuela

the Engineering and Construction phases of the Complejo Criogénico de

Occidente (CCO) which will replace old obsolet plants with state-of-the-art

gas processing plants with a total capacity of 950 MMSCFD feedgas with a

98% Ethane recovery from plant feedstock.

The total natural gas liquids fractionation capacity for the CCO will be as of

35000 BPD and the design liquid production will be 60000 BPD, therefore

unprocessed liquids will be sent to Ulé and Bajo Grande fractionation plants

(18000 BPD and 7000 BPD respectively). According to this, it is required to

analyze the process behavior of the new operation scheme under the new

NGL feedstock characterization. The main objective of this research is to

define an advanced control strategy that will meet the new process conditions

of the debutanizer tower V-303 of the Bajo Grande fractionation plant.

Because there is always possible to have process disturbances, it is

necessary to determine which of them could affect the fractionation tower and

propose the best-suited control strategy for the process.

Results will be presented as well as objectives fullfilment; first of all a

process analysis will be done to determine which variables may produce

disturbances in the process, then steady state and dynamic simulations will

be done to obtain process data required as function of controlled and

disturbance variables. A third phase allowed to identify obtained data from the

previous phase in order to develop a mathematical model representative of

each case study. For this purpose the ARX and JB models were used as well

as mass and energy balances. Starting from the calculated transfer equations

advanced control strategies were designed to finally choose the best choice

for the case study.



This research allowed to generate data and observe the process behavior

of the system which helped to foresee, design and develop the advanced

control strategies to maintain quality standards of the fractionated products. It

was possible to achieve through system identification techniques, to simulate

obtained data and produce mathematical models adapted to every case study

and finally advanced control strategy were designed to select the best one.

METHODOLY OF INVESTIGATION The methodology was based in five stages involving different activities with

the purpose of achieving every specific objective and, therefore, the general

objective. It was considered the sequence structure developed by Querales

(1999), nevertheless, author oriented every stage of the investigation to the

conditions of the facility being studied.

Next, every stage will be discussed:

STAGE I: Defining process variables affecting products quality. Process variables affecting the quality of the fractionated products will be

identified by means of Process Flow Diagram (PFD) and operations

philosophy of the debutanizer tower V-303 from operation manual of the Bajo

Grande fractionation plant. The related process variables having the most

influence on products quality for both top (buthane) and bottom (natural

gasoline) of the tower were used to present possible process schemes and

more critical affectations to the process.

STAGE II: Obtaining process data through dynamic state simulation. In this stage, process behavior will be simulated by means of Hysys V. 3.2

software considering the process affectations identified in the previous stage

for every case study, introducing step-wise disturbances in open loop and

considering dynamic process condictions. Data adquired will be stored

continuously.



STAGE III: Developing process mathematical models through system identification.

Data adquired in the previous stage will be used alongside system

identification techniques in order to develop mathematical models

represented by transfer equations in La Place domain for each case study to

develop equations representing the variable response to a specific

disturbance.

STAGE IV: Designing advanced control strategies adapted to the process.

Different control strategies will be designed by using block diagrams and

developed with software Matlab 7.0.1 in order to set controller adjusment,

starting from transfer equations developed in the previous stage.

STAGE V: Selecting advanced control strategy ensuring system stablity.

From the different responses obtained for every type of controller, it will be

evaluated and selected the one offering the best and fastest response to

process disturbances and giving the least dead time.

PROBLEM APPROACH Venezuela is a big energy producing country, with large crude oil and gas

production facilities worlwide. In this way, natural gas from crude oil reservoirs

has been exploited and sent to production flow stations to be separated from

the oil and then processed in the compression and extraction plants in order

to obtain different gas compounds, such as Methane, Ethane, Propane,

Butane and Natural Gasoline.

Currently, natural gas liquids (NGL) processing plants in western

Venezuela are Lamar liquido, Lama Proceso, LGN I/II from Complejo Ana

María Campos, Tía Juana 2 and Tía Juana 3. These processing facilities

extract the main components of natural gas which is the raw material for the

fractionation plants in Bajo Grande and ULE. Here, Natural Gas Liquids are



separated into different products such as Propane, Buthane, Normal Buthane,

Iso Buthane and Natural Gasoline which then are distributed to national and

international markets.

Now a days, PDVSA GAS is heading the Complejo Criogénico de

Occidente proyect (CCO) which will replace 5 NGL extraction plants

mencioned before with the exception of Lama Proceso plant. This complex

will implement state-of-the-art technology to recover 98 per cent of Ethane in

the NGL feed stream.

In this new vision, feedgas for the Bajo Grande fractionation plant will be

supplied by Lama Proceso plant and the CCO complex, changing the former

feed scheme in which NGL was supplied by Lamarlíquido, Lama Proceso and

LGN I/II from Ana María Campos complex.

In Bajo Grande plant it is achieved the fractionation of the NGL in a

distillation train known as Área 300, then the fractionated products are stored

in refrigerated tanks and floating-roof tanks according to the characterístics of

each product (this is called area 500), to finally be dispatched through NGL

tankers at the loading dock facility (Area 600), truck tanker facility and

Pequiven with a design process capacity as of 25.600 bbl per day.

To achieve this production figure, there are several distillation columns that

separate NGL into its components. One of these columns is the debutanizer

tower V-303 whose funtion is to separate the butane mix (C4+) from the

heavier components (usually known as natural gasoline).

In order to implement the operational changes described before, it is

necessary to evaluate the disturbance variables that might affect products

quality for both top (Buthanes) and bottom (Natural Gasoline) in the

debutanizer tower and the operation philosophy and separation control

process because the feed composition of the NGL stream will change once

the Complejo Criogénico de Occidente is commissioned.

Fractionated products from this colummn must meet quality standards

which allow them to be dispatched to the different markets nationally and



internationally. Off specification product is undesirable and limits its purchase

possibilities from potenctial buyers, decreasing selling prices and increasing

operational costs.

By the above, it is necessary to maintain operational parameters of the

fractionation columns and related equipment. This is performed by a routinary

team work between the process control engineer and the operations

personnel. It is also necessary to perform continuous analyses of the

fractionated product chromatography in order to execute corrective actions

(generally in the manual way) to ensure product quality and avoid economical

losses. This is why it is important to design an advanced control strategy

capable of minimizing disturbing effects to product quality obtained in the

debutanizar tower V- 303. Knowing that the stability of the process variables

of any given production plant is the basic parameter to achieve optimum

quality products, energy saving and production increase, which eventually

leads to a more competitive and profitable facility. A successful control

strategy is undoubtedly, one of the fundamental factors in achieving such

benefits.

OBJECTIVES GENERAL OBJECTIVE

To design an advanced control strategy to minimize disturbing effects on

quality of products obtained in a debutanizer tower.

SPECIFIC OBJECTIVES

• Defining process variables affecting products quality.

• Obtaining process data through dynamic state simulation.

• Developing process mathematical models through system

identification.



• Designing advanced control strategies adapted to the process.

• Selecting advanced control strategy ensuring system stablity.

RESULTS AND ANALYSIS STAGE I: Defining process variables affecting products quality

Figure 1 shows a Process Flow Diagram of the debutanizer system once

the CCO is commissioned and its related control loops:



Source: Basic Engineering Feed 98% CCO Figure 1. Process Flow Diagram of the Debutanizer System



This research attempts to control necessary process variables to maintain

top-and-bottom normal operation temperature conditions to guarantee

product quality for both butane mix (C4+) on top of the column and natural

gasoline at the bottom. It is observed that several disturbances may affect

product quality, among them flow and temperature of the feed stream, inlet

gas characterization and pressure variations through the tower.

Another important consideration is the process analysis to changes in NGL

composition of the feedstream; however it is known the fact that response

time to disturbances in processes where corrective actions depend on online

chromatographic analyses is very slow. Because of this, it will not be taken

into consideration for the analysis and solution of this problem. Aditionally,

protection for pressure changes in the distillation column is provided (PRC-

306) for off range pressure values, for which this variable will also be

discarted.

Different scenarios will be analized in order to observe top-and-bottom

temperature behavior, hot oil control valves and tower refflux, through the

following case studies:

• Evaluation of a step-wise disturbance in the feed stream temperature

related to temperature at the top of the column.

• Evaluation of a step-wise disturbance in the feed stream of the tower

related to temperature at the top of the column.



• Evaluation of a step-wise disturbance in the feed stream of the tower

related to temperature at the bottom of the column.

• Evaluation of a step-wise disturbance in the feed stream temperature

related to to temperature at the bottom of the column.

• Evaluation of a step-wise disturbance in the reflux flow related to

temperature at the top of the column.

• Evaluation of a step-wise disturbance in the hot oil in the reboiler related

to temperature at the bottom of the column.

• Evaluation of the reflux control valve of the debutanizer tower V-303.

• Evaluation of the hot oil control valve in the reboiler of the column.

2. STAGE II. Obtaining process data through dynamic state simulation

To obtain necessary data to develop mathematical models it was used the

process simulation software Hysys, provided that the objective of the

investigation is to design an advanced control strategy in the debutanizer

tower V-303 when the CCO complex is commissioned and and feeding the

Bajo Grande fractionation plant. Actual data could not be obtained at this

time.

In this stage all of the scenarios named in the former stage were process-

simulated in dynamic state. All of the data obtained was registered in constant



time intervals for every scenario and was storaged in excel files. This

information will be used to develop the transfer equations for everyone of the

scenarios involved.

For this simulation it was used the SRK EOS package because of its wide

range of applicability for the hydrocarbon property calculation.

Once the steady-state simulation was completed it was possible to obtain

the characterization of the gas feedstream to the debutanizer tower and with

this information it was built the process model for the debutanizer tower.

After defining the disturbing variable and disturbed variable the dynamic

state simulation was performed. There were stablished initial and final times

in order to register in an automatic way the data generated by the simulator in

a defined time interval. This data was stored in the database and exported to

an Excel file to serve as input for identifying every one of the systems in the

next stage.

3. STAGE III: DEVELOPING PROCESS MATHEMATICAL MODELS

THROUGH SYSTEM IDENTIFICATION.

After obtaining all of the data from the different simulations, it was used the

commercial software MATLAB to get the mathematical representación of the

model through transfer equatons for every case study. It will only be

showcased the step-by-step procedure for Case 1 provided that the same

procedure will be used the rest of the cases.



3.1. CASE 1: ESTIMATION OF DYNAMIC MODEL USING THE

FEEDSTREAM TEMPERATURE AS DISTURBING VARIABLE AND

VALIDATING TEMPERATURE BEHAVIOR ON TOP OF THE

DEBUTANIZER TOWER V-303.

Utilizing simulation software ident, it was obtained the best representation

using the parametric modet ARX whose results were (4 4 1).

Figure below compares step-wise inlets introduced in the manipulated

variable: feedstream temperature and the outlet represented by the top

temperature behavior.

Source: Author 2009

Figure 2: Inlet and Outlet Signals



The best representation of the models applied can be appreciated in figure

3 with an 80% approximation to the actual data.

Source: Author 2009 Figure 3: ARX Model Approximations

It was also simulated utilizing the following Matlab commands:

load c:\ttopetalim.prn

y1=ttopetalim(:,2);u1=ttopetalim(:,1);

z1=[y1(1:180) u1(1:180)];z2=[y1(181:360) u1(181:360)];

idplot (z1);

Figure 4 shows the inlet value graphic: feedstream temperature called u1

and outlet variable: top temperature called y1, such graphic presents a similar

behavior to the figure obtained with the ident software.



Source: Author 2009 Figure 4: Inlet and Outlet signals Graphics

z1d=detrend(z1);z2d=detrend(z2);

%Ident values were used

th=arx(z1d,[4 4 1]);

th=arx(z2d,[4 4 1]);

y=detrend(y1(181:360));u=detrend(u1(181:360));yh=idsim(u,th);plot([yh y]);

present(th);

Discrete-time IDPOLY model: A(q)y(t) = B(q)u(t) + e(t)

A(q) = 1 - 1.742 (+-0.07497) q^-1 + 1.074 (+-0.1482) q^-2 - 0.4148 ( +-

0.1419) q^-3 + 0.12 (+-0.06283) q^-4

B(q) = 0.0341 (+-0.0002158) q^-1 - 0.02855 (+-0.002556) q^-2

+ 0.01045 (+-0.003224) q^-3 - 0.005209 (+-0.002395) q^-4



Source: Author 2009 Figure 5: Validation of Data

[NUMd,DENd]=th2tf(th)

NUMd =

0 0.0341 -0.0285 0.0104 -0.0052

DENd =

1.0000 -1.7422 1.0744 -0.4148 0.1200

[NUMc,DENc]=d2cm([0 0.0341 -0.0285 0.0104 -0.0052],[1 -1.7422 1.0744

-0.4148 0.12],15,'zoh')

NUMc =

0 0.0025 0.0003 0.0000 0.0000

DENc =

1.0000 0.1414 0.0151 0.0004 0.0000

f=tf(NUMc,DENc)

Transfer function:



L NTxi NTh NT

M Bxi Bh B

Bxi Bh B

V NT+1yi Nt+1H Nt+1

F ST S

T SS

Fondo de la Torre V-319

0.002461 s^3 + 0.0003103 s^2 + 3.531e-005 s + 6.766e-007

-----------------------------------------------------------------------------------

s^4 + 0.1414 s^3 + 0.01514 s^2 + 0.0003999 s + 2.343e-006

3.6. CASE 6 PROGRAM FOR ESTIMATING TRANSFER EQUATION OF

THE HOT OIL FLOW THROUGH REBOILER RELATED TO THE

TEMPERATURE OF THE BOTTOM OF THE DEBUTANIZER TOWER V-

303.

Performing energy and mass balances at the bottom of the tower V-303

and neglecting dynamics of the rerebolier E-304 (see Figure 55), it gives:

Source: Corripio (1991)

Figure 6: Variables to consider in the mass and energy balance of a distillation column



][11 SSSSSNTNTBNTNTB

B TTCpFHVBhhLdt

dhM −+−−= ++

(1)

Assuming ∫= CpTdTh and making Tref=0.

][11 SSSSSNTNTBBNTNTNTB

BB TTCpFVTBCpTCpLdt

dTCpM −+−−= ++ λ

(2)

Normalizing ecuation (2), it yields:

BM B

p =τ (2.1)

B

NTNT

BCpLCp

Kp =1

(2.2)

B

NT

BCpKp 1

2+=

λ

(2.3)

B

SSSS

BCpTTCp

Kp][

3−

= (2.4)

Then:

SNTNTBB

p FKpVKpTKpTdt

dT3121 +−=+ +τ

(3)

Equation needed is the bottom temperature related to the hot oil

flow, )()(

SFST

S

B

, therefore:



SBB

p FKpTdt

dT3=+τ

(4)

Applying Laplace t ecuation (4), we have:

1)()( 3

+=

SKp

SFST

pS

B

τ ( 5)

Where the time constant is represented in ecuación (2.1) and the process

gain represented by ecuation (2.4).

Where:

MB: is the liquid hold-up de in the bottom of the tower (1314 lbmol).

B: Molar flow of the bottom product of the tower (450,6 lbmol/h).

CpB: Specific Heat of the bottom of the tower (54,48 BTU/lbmol°F).

CpS: Specific Heat of the Hot Oil (153,4 BTU/lbmol°F).

TS: Oil inlet temperature (400 °F).

TSS: Oil outlet temperature (300 °F).

All values for the parameters calculation were obtained by process

simulation at design conditions of the debutanizer tower. Replacing each one

and calculating:

12916.06212.0

)()(

+=

°SBPDF

FT

S

B (6)



Equation above represents the transfer function of the bottom temperature

(TB) related to the hot oil flow through the rebolier of the the tower V-303.

3.7. CASE 7 CALCULATION OF THE TRANSFER EQUATION OF THE FLOW CONTROL VALVE 33FV – 309 FOR THE VOLUME FLOW CONTROL OF THE TOWER REFLUX.

Considering information supplied by representatives from the Fisher

valves, the following data was obtained:

6796.0min119.0

40224max

===

=Δ=

ravityGspecificgimerodstroketts

psigPCV

Control valve gain:

75.17186796,040*224* =≡=≡

Δ= KvKv

GespPCvKv

Calculated gain substitutes in the transfer function, according to proposed

by Corripio (1991).

1119.075.1781

1 +=≡

+=

sGv

tsKvGv

3.8. CASE 8 CALCULATION OF THE TRANSFER EQUATION OF THE FLOW CONTROL VALVE 33FV – 329 FOR HOT OIL FLOW CONTROL THROUGH REBOILER E-304

Process and control valves data:

6796.0min153.0

40170max

===

=Δ=

avitySpecificgrGimerodstroketts

psigPCV



Control valve gain:

13.13046796.040*170* =≡=≡

Δ= KvKv

GespPCvKv

Replacing the valve gain in the transfer function:

1153.013.1304

1 +=≡

+=

sGv

tsKvGv

Once indentified the case studies, it is presented a summary table showing

all of the transfer functions obtained.

Table 1: Transfer Functions representing process dynamics of the debutanizer tower V-303

Variables Functions

Top Temperature related to feedstream temperature

(°F/°F) 1170646160350426803

28.0151321050234

23

+++++++

sssSsss

Top Temperature related to feedstream flow (°F/BPD) 114618881212045496

3623342751234

23

+++++++

sssSsss

Bottom temperature related to feedstream flow

(°F/BPD) 17.23257.3153

0041.00592.02 ++−

sSs

Bottom temperature related to feedstream temperature

(°F/°F) 13561095165797881057

23.039.578.035.357234

23

++++++−

sssSsss

Top Temperature related to reflux flow (°F/BPD) 1213,701,17228,958,10676,0

122,653,512,12536,56586,62345

234

+++++−−−−−

sssssssss

Bottom temperature related to hot oil flow through the

reboiler (°F/BPD) 12916.0

6212.0+S



Reflux flow related to current intensity (BPD/mA) 1119.0

75.1781+S

Hot oil flow related to current intensity (BPD/mA) 1153.0

13.1304+S

Source: Author 2008

4. STAGE IV. DESIGNING ADVANCED CONTROL STRATEGIES

ADAPTED TO THE PROCESS.

In this section it will be shown the proposed strategies that might provide

process control, i.e., to operate in an optimal way debutanizer tower V-303.

4.1. CONTROL STRATEGY DESIGN FOR COLUMN BOTTOMS

Control systems proposed to ensure product quality at the bottom of the

column are shown below.

4.1.1 CASCADE CONTROL OF THE BOTTOM TEMPERATURE WITH HOT

OIL FLOW THROUGH REBOILER E-304.

This strategy pretends to istablish a cascade control loop where a

temperature control set at 210°F sends a signal to a hot oil flow control loop

to manipulate flow valve FV-329, using an automatic control instead of the

manual control being used currently in the Bajo Grande fractionation plant.

For block diagram shown in figure 60 it was concluded the process transfer

function related to the bottom temperature variation with hot oil flow through

the reboiler.



12916,06212,0)(

+=

sslerGvalvreboi

To obtain parameters for the PID2 controller, it was used the Ziegler-

Nichols criterion. Taking curve S of the system response in open loop it gives

a delay time of L=0,14 and a time constant ζ=0,685. Therefore, from Ziegler-

Nichols equatons it is obtained:

87,514,0685,0*2,1*2,1 ===

LK p

τ

97,10*2

==L

KK p

i

41,0)*5,0( == LKK pd

However these values were depured to obtain a better response, getting

finally:

Kp=7

Ki=12

Kd=0,75

Introducing these parameters in the PID2 controller the process response

stabilizes in less than 2 seconds at 210°F. With this strategy it can be

achieved a good attunement for the loop, as can be appreciated in Figure 7.



Fuente Autor (2009)

Figure 7: Response for the cascade controller of the flow at the bottom of the column V-303

4.1.3. FEED FOWARD CONTROL AT THE BOTTOM OF THE COLUMN

WITH FEEDSTREAM FLOW AS DISTURBING VARIABLE

It is required to evaluate a feed forward control loop to balance the effect of

the temperature change at the bottom of the tower when a perturbation in the

feedstream occurs.

It will be used the transfer function obtained in stage 3 which relates the

affectation of the bottom temperature when the feedstream flow is disturbed.

Such equation will be reduced to a less-order system to make calculations

easier.

17,23257,31530041,00592,0)( 2 ++

−=

ssssGpert



)06951,0)(0045,(10*)006949,0(18776,0)(

5

++−

=−

ssssGpert

In order to design the feedfoward controller it is necesaary to reduce the

order of the transfer function related to the feedstream flow disturbance.

Assuming as the principal pole the value of 0,0045 and ensuring the static

gain will fit as much as possible after the reduction, it can be concluded that

the reduced transfer function will be:

0045,0103096,1)(

5

+=

−

sxsidedGpertreduc

For the calculation of the transfer function of the Feed Forward controller, it

is known that,

)()()(sGprocess

sGpertsdGfeedfowar −=

Where,

)(*)(1 slerGvalvreboisGGprocess =

⎟⎠

⎞⎜⎝

⎛+⎟⎟

⎠

⎞⎜⎜⎝

⎛+++

+=

12916,06212,0*

)5,2)(5,3)(5()17,13(0224,2

sssssGprocess

In a similar way it is necessary to reduce the order of the transfer function

of the process in order to design the feedfoward controller, taking the main



pole as 2,5 and keeping the static gain, it can be ontained the desired

reduction:

5,25623,1+

=s

Gprocess

06921,0)515,2(107484,0

5,25623,1006951,0

101693,1

)(5

5

++

−=

+

+−=−

−

ssx

s

sx

sdGfeedfowar

Figure 8 showcases the controller response of the example. The response

can be stabilized in the value of 210°F for the first loop, in the second loop a

perturbation of 5 was introduced and the controller could handle such

fluctuation quickly keeping control in the valve.

Source: Author (2009)

Figure 8: Response of the Feed forward Controller at the bottom of the tower with feedstream flow as perturbation variable.



4.1.4. FEED FOWARD CONTROL AT THE BOTTOM OF THE

DEBUTANIZER TOWER WITH FEEDSTREAM TEMPERATURE AS

DISTURBING VARIABLE

In this case it will be evaluated the column feedstream as perturbation

parameter. The objective is to know the controller behavior for this kind of

disturbance.

Transfer function obtained in stage 3 will be used to relate bottom

temperature affectation when feedstream temperature is disturbed. This

equation will be reducided to a less-order system to make calculations easier.

1356109516579788105723,039,578,035,357)(2 234

23

++++++−

=ssss

ssssGpert

)01093,003808,0)(003099,0)(0335,0()01665,004081,0)(03863,0(004058,0)(2 2

2

+++++−+

=ssss

ssssGpert

Taking 0,008099 as the main pole and keeping the static gain the transfer

function can be reduced to get:

003099,0101015,7)(2

4

+=

−

sxsidedGpertreduc

For the calculation of the Feed Forward controller transfer function, it is

known that,



)()(2)(

sGprocesssidedGpertreducsdGfeedfowar −=

Where,

)(*)(1 slerGvalvreboisGGprocess =

003099,0)101432,1105456,4(

5,25623,1003099,0

101015,7

)(34

4

++

−=

+

+−=−−

−

sxsx

s

sx

sdGfeedfowar

Figure 9 represents the controller response achieving stabilization in the

referenced value of 210°F, in the second loop a perturbation of 5 was

introduced and the controller could handle such fluctuation quickly keeping

control in the valve.


Figure 9: Response of the PID controller for the bottom flow of the column V-303



4.1.5. FEED FOWARD CONTROL AT THE BOTTOM OF THE COLUMN

WITH FEEDSTREAM OF THE TOWER AS DISTURBING VARIABLE

This last control strategy covers the former two evaluations. It is desired to

check if the controller will be able to maintain process conditions facing

different disturbances at tower inlet stream.

The block diagram does not show any new calculated parameter. There

were added the two process signals to the flow and temperature trasmitters at

controller inlet to make them both be taken into account by the controller in

order to have a correct response to any disturbance of the process variables.

Disturbances were introduced after 5 seconds approximately and the

behavior shown in figure 10 corroborates it. Results given by this strategy

fully meets process needs.

Figure 10: Response of the PID controller for the bottom flow of the column V-

303



4.2. CONTROL STRATEGY DESIGN FOR THE TOP OF THE COLUMN.

Control systems proposed for product quality control at the top of the

column are presented below.

4.2.1 CASCADE CONTROL FOR TOP TEMPERATURE WITH REFLUX

FLOW.

This strategy is intended to calculate parameters for a cascade control

system in which a temperature control set at 128°F sends a signal to a reflux

flow control loop for the valve FV-309, utilizing pneumatic control instead of

the manual control being used currently in the Bajo Grande fractionation

plant.

1213,701,17228,958,10676,0122,653,512,12536,56586,6)( 2345

34

+++++−−−−−

=sssss

ssssGreflux

)08016,05214,0)(52,2)(679,4)(65,15()0619,048785,0)(91,2)(16,5(4275,97)( 2

2

+++++++++−

=ssssssssssGreflux

Due to the closeness among some zeros and poles of the transfer function

above, it is desirable to reduce system order keeping the static gain. The

reduced system is as follows:

65,1542,97)(

+−

=s

sfluxGreducedre

In order to obtaine the parameters for the PID2 controller shown in the

block diagram from figure 15, it is proceeded to resolve the array.



065,15

4201,97)6)(4(

)0395,15(5961,1)(12

=⎥⎦

⎤⎢⎣

⎡+

−⎥⎦

⎤⎢⎣

⎡++

+⎥⎦

⎤⎢⎣

⎡ +++

ssss

sKiKpsKds

For working with a more simplified system it is proceeded to discard the

pole-and-zero set around the value of 15. Finally, the resulting function is a

three-order equation, as shown below.

0492,155)24492,155()10492,155( 23 =−+−++−+ KisKpsKds

Using the pole positioning technique for a third-degree system with a

characteristic function as shown below:

321)323121()321( 23 PPPsPPPPPPsPPPs +++++++

Assuming P1=5, P2=10 y P3=15, yields:

Kp=1,6142

Ki=4,8234

Kd=0,1286

However, these results were depured to obtain a best-suited response to

get:

Kp=0,75

Ki=3,5

Kd=0,133



Introducing theses parameters in the PID2 controller, process response

stabilizes in less than two seconds at the value of 128°F. This made possible

to achieve a good loop attunement.


Figure 16: Response of the cascade controller for the top flow of the Column V-303

4.2.3. FEED FORWARD CONTROL AT THE TOP OF THE COLUMN WITH

FEEDSTREAM OF THE TOWER AS DISTURBING VARIABLE

In this case it is required to evaluate a feed forward control set to

counteract the effect of the top temperature change when a disturbance in

feedstream flow of the tower occurs.



The transfer function obtained in stage 3 relating the affectation of top

temperature with the feedstream flow of the tower will be used. This equation

will be reduced to a less-order system to make calculations easier.

1146188812120454963623342751)( 234

23

+++++++

=ssss

ssssGpert

)0228,01312,0)(1277,0)(007552,0()01886,006359,0)(05782,0(060467,0)( 2

2

+++++++

=ssss

ssssGpert

Reducing order:

007552,003628,0)(

+=

ssedGpertreduc

For the calculation of the transfer function for the Feed Forward controller,

it is known that,

)()()(sGprocess

sGpertsdGfeedfowar −=

where,

)(*)(1 sfluxGreducedresGGprocess =

49151,24

65,1542,97*

)6)(4()04,15(5961,1

+−

≈⎟⎠

⎞⎜⎝

⎛+−

⎟⎟⎠

⎞⎜⎜⎝

⎛++

+=

sssssGprocess



007552,0)4(10456,1

49151,24

007552,003628,0

)(3

++

≈

+−+−

=−

ssx

s

ssdGfeedfowar

Figure 11 represents the controller response showing stabilization in the

referenced value of 128°F. After 7 seconds it was introduced a disturbance in

the feedstream flow and the controller could handle such fluctuation quickly

keeping control in the valve.


Figure 11: Response of the Feed Forward controller at the top of the tower

with feedstream flow as disturbance

4.2.4. FEED FOWARD CONTROL AT THE TOP OF THE COLUMN WITH

FEEDSTREAM TEMPERATURE OF THE TOWER AS DISTURBING

VARIABLE



The transfer function obtained in stage 3 relating the affectation of the top

temperature with the feedstream temperature will be used. This function will

be reduced to a less-order system to make calculations easier.

117064616035042680328,0151321050)(2 234

23

+++++++

=ssss

ssssGpert

)1134,01083,0)(02482,0)(008322,0()01198,010355,0)(02225,0(0024602,0)(2 2

2

+++++++

=ssss

ssssGpert

Reducing order:

005322,01041,2)(2

3

+=

−

sxsidedGpertreduc

For the calculation of the transfer function for the Feed Forward controller,

it is known that,

)()(2)(

sGprocesssidedGpertreducsdGfeedfowar −=

Where,

)(*)(1 sducedGreflujoresGGprocess =

008322,0)4(106768,9

49151,24

008322,010411,2

)(5

3

++

=

+−+

−

=−

−

ssx

s

sx

sdGfeedfowar



Figure 12 represents the controller response showing stabilization in the

referenced value of 128°F. After 3 seconds it was introduced a disturbance in

the feedstream temperature of the tower and the controller could handle such

fluctuation quickly keeping control in the valve.


Figure 12: Response of the Feed Forward controller at the top of the tower with feedstream temperature as disturbance

4.2.5. FEED FOWARD CONTROL AT THE TOP OF THE COLUMN WITH

FEEDSTREAM OF THE TOWER AS DISTURBING VARIABLE

This last control strategy covers the former two evaluations. It is desired to

check if the controller will be able to maintain process conditions facing

different disturbances at tower inlet stream.

The block diagram does not show any new calculated parameter. There

were added the two process signals to the flow and temperature trasmitters at



controller inlet to make them both be taken into account by the controller in

order to have a correct response to any disturbance of the process variables.

Disturbances were introduced at different times (temperature at 3 seconds,

flow at 7 seconds) and the behavior shown in figure 13 corroborates it.

Results given by this strategy fully meets process needs.


Figure 13: Response of the Feed Forward controller at top of the tower with disturbances in feedstream flow and temperature

5. STAGE V: SELECTING ADVANCED CONTROL STRATEGY ENSURING

SYSTEM STABLITY.

The block diagram of the proposed control strategy for the debutanizer

tower V-303 was conformed by a Feed Forward controller (FFC1 and FFC2)

at the top of the tower.

The top temperature controller of the tower V-303 receiving signal from the

feedforward controller is the primary or master controller of a cascade control



loop with a PID action. The primary controller sends a signal to the secundary

or slave controller (with a PI action) of a flow control loop to settle the flow

rate passing through the reflux control valve FV-309.

In the same way, at the bottom of the column, flow and temperature

signals going to the bottom temperature controller of the tower are corrected

by a feed forward controller (FFC3 and FFC4), that actuate directly over the

set point of the bottom temperature controller.

The bottom temperature controller of the debutanizer tower V-303

receiving signal form the feed forward controller is the Master o primary

controller of a cascade control system. This controller has a PID action. The

primary controller sends a signal to the secondary or slave controller (with PI

action) of a flow control loop, to settle the the flow rate passing through the

the reflux control valve FV-309.

Its block diagram representation can be appreciated on figure 14.



Source: Author (2009) Figure 14: Block Diagram Representation of the Designed Control Strategy



The proposed secondary controller of the reflux flow control loop for the top of

the tower has a PI action; therefore it was necessary to determine its gain and

controller integral time for design purposes. For the calculation of each parameter,

the obtained transfer functions were equalized with the corresponding first-order

canonical form, second order or greater.

Then, computing with the MATLAB SIMULINK software there were obtained the

best-suited values producing the best response for the control loop.

The parameter calculation for the primary or master controller (PID) at the

bottom of the tower, it was used the closed loop method (Ziegler-Nichols method),

thus finalizing controller design.

The response of the feed forward controller at top of the column stabilizes at

128°F and quickly to any occurring disturbance. See figure 15.


Figure 15: Response of the Proposed Control Strategy for the Top of the Tower


Gerencia de Procesamiento de Gas Occidente Gerencia de Procesamiento de Gas Occidente Gerencia de Procesamiento de Gas Occidente

The feed forward controller response for the bottom of the tower stabilizes at

210°F, according to adjusment and quickly responds to any occurring disturbance.

See figure 16.


Figure 16: Response of the Proposed Control Strategy for the Bottom of the Tower

Each controller equation can be seen in Table 3.



Table 3: Feed Forward Controller Transfer Functions Corresponding to Proposed Control Strategy for Debutanizer Tower V-303

Controller Transfer Function

Temperature Controller for the Top of the Tower with PID

action(mA/mA)

⎟⎠⎞

⎜⎝⎛ ++ 63,531,26*133,0

Ss

Flow Controller for the Top of the Tower with PI action (mA/mA) ⎜⎜

⎝

⎛⎟⎠⎞+−

Sx 03,151*10066,1 4

Temperature Controller for the Bottom of the Tower with PID action

(mA/mA)

⎟⎠⎞

⎜⎝⎛ ++ 3,99*75,0

Ss

Flow Controller for the Bottom of the Tower with PI action (mA/mA) ⎜⎜

⎝

⎛⎟⎠⎞+−

Sx 25,101*1043,1 4

Source: Author 2009

For designing feed forward controller (FFC1 and FFC2) or for calculating

transfer function for each controller, it was necessary to solve the block algebra of

the control proposal relating the controlled variable (top temperature), manipulated

variable (reflux flow) and secondary controller, with disturbing variables

(feedstream flow and temperature).

For designing feed forward controller (FFC3 y FFC4), it was necessary to solve

the block algebra of the control proposal, relating the controlled variable (bottom

temperature), manipulated variable (hot oil flow), and secondary controller, with

disturbing variables (feedstream flow and temperature). See Table 4.



Table 4: Feed Forward Controller Transfer Functions for the Proposed Control Strategy for Debutanizer Tower V-303.

Controller Transfer Function

Feed Forward Controller at the Top with Feedstream Flow Disturbances 007552,0

)4(10456,113

++

=−

ssxFFC

Feed Forward Controller at the Top with Feedstream Temperature

Disturbances 008322,0

)4(106768,925

++

=−

ssxFFC

Feed Forward Controller at the Bottom with Feedstream Flow

Disturbances 06921,0

)515,2(107484,035

++−

=−

ssxFFC

Feed Forward Controller at the Bottom with Feedstream

Temperature Disturbances 003099,0

)515,2(105456,444

++−

=−

ssxFFC




CONCLUSIONS

Flow and Temperature disturbances at Inlet stream are the most easily

controlling variables, provided that column control systems present overpressure

protections.

Debutanizer Tower V-303 keeps the same design operation conditions even

when the new feedstream coming from CCO will have different characterization.

It is possible to obtain gas characterization using process simulation software

as well as, anticipately knowing system behavior to any occurring disturbance.

For obtaining transfer functions representing different scenarios, system

identification with models ARX y BJ was used, as well as mass and energy

balances for calculating control valve equatons with design data.

Temperature at the top of the debutanizer tower V-303 rises when bottom

temperature of the tower increases, and decreases with reflux flow increase. For

feedstream flow and temperature changes, bottom temperature remains almost

constant.

PI controllers resulted to be effective for flow control on the hot oil and tower

reflux valves.

Cascade control gave good response keeping top and bottom temperatures.

Feed Forward controllers showed a fast response when changes in the

manipulated variables were introduced: feedstream flow and temperature, quickly

stabilizing at the reference values given.

The primary control resulted to be an Integral Proportional Control PI and the

cascade control was the secondary control with Integral, Proportional and

Derivative constants PID.

The designed control strategy allowed mitigating feedstream temperature and

flow perturbations both at the bottom and top of the tower, keeping stablished set

points and therefore achieving product quality.

Feed Forward control strategy allows compensating feedstream flow and

temperature variation effect on top and bottom temperature.



RECOMMENDATIONS

To analize control systems for each fractionation column before doing

modifications affecting the correct performance of it and propose a feasible option.

To use process simulation software when it is not possible to adquire

physical data from actual process, provided that it was proved to help predecting

process behavior to any occurring disturbance.

To use Integral Proportional or Cascade controls in process or systems

having less than three associated variables.

To use PI control in process where the controlled variable is to be

temperature because it is proven to have a faster response.

To use cascade control when it is necessary to control processes not

affectaded by several variables.

To use feed foward control when there is more than one disturbing variable

because it is proven to give good results.

To use this methodology for investigating and designing control strategies

for the rest of the distillation columns of the Bajo Grande fractionation plant.

To do new investigations based on different control schemes, for example,

adaptative control, robust control or neural networks, to compare performance of

each controller to the same conditions.



BIBLIOGRÁFIC REFERENCES

Acedo Sánchez,José (2003). Control Avanzado de Procesos.

Amaya Ennis, (1994). Control de Procesos II.

Chávez, Nilda (1994). Introducción a la investigación educativa.

Corripio, Smith. (1991). Control Automático de Procesos, 1º edición. México.

Creus, Antonio. (1997). Instrumentación Industrial, 6° edición, Alfaomega

marcombo. México.

Dahling, E. Desing and Tuning Digital Controlers. Instruments and Control

Systems. 1968.

Hernández (1998). “Metodología de la investigación”, México.

Manual de Operaciones de la Planta de Fraccionamiento GLP Bajo Grande.

Ogata, Katsuhiko. (1998). Ingeniería de control moderna. 3° edición. Prentice Hall.

México.

Pages S. Buckley, William L. Luyben, Joseph P. Shunta (1985) Design of

Distillation Column Control Systems

Shinskey (1998) Sistemas de Control de Proceso. 1º edición. Editorial Mc Grawhill

William Luyben process modeling simulation and control for quemical engineers.

Second Edition 5.

Revistas

Rivera, Daniel. Process Dynamics and Control; Introduction to Internal Model

Control with Application to PID Controller Tuning. 1999.

Normas

URBE. Manual de Trabajo de Grado y Tesis Doctoral. Maracaibo. 2004.

Manuales

Ledezma, O. (2000). Evaluación – Económica de Proyectos de Automatización.

Universidad Corporativa CIED. Venezuela.

Referencias electrónicas

Control automático del proceso productivo J. Mario Domínguez Valcárcel.

Documents

16 14 Advance control in a Debutanizer PDVSA · PDF file2 ADVANCED CONTROL STRATEGY DESIGN TO MINIMIZE DISTURBING EFFECTS ON PRODUCT QUALITY IN A DEBUTANIZER FRACTIONATION COLUMN Gerencia