Sheh Muhammad Afnan ( Eh2215a) Control Loop Simulation Report

1 2 3 4 5 7

6 UNIVERSITI TEKNOLOGI MARA

8

FAKULTI KE KEJURUTERAAN KI KIMIA

9

CHEMICAL PROCESS CONTROL 10

11 12 1 13 14 2 15 & 16  17 5 18 6 19 7 20 8 21 9 22 23 24 25 26 27 28 29 30 31 &2 33 34 35 ----&6 &7 &8 39 40 41 42 43

NAM NAME STU,ENT I, ,ATE SU/MIT SEMESTER PROGRAMME  CO,E GROUP ASSIGNMENT SU/MIT TO

(CPE562)

% SHEH MUHAMMA, AFNAN /IN SEH HANAFI % 201&210&82 % 75122015 %5 % EH221 % EH2215A % CONTROL LOOP SIMULATION % SIR MOH, AI-A, AHMA,

Re!"#

%$C'e#e *+%

Re'e#e *+%

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

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

(SIR MOH, AI-A, AHMA, ) )

(

,!.e%

,!.e%

44

CHAPTER 1 : INTRODUCTION

45

History of PID controller

46

PID also known as proportional–integral–derivative controller is a control

feedback mechanism. In early years, PID controller is used as automatic ship steering.It was implemented as a mechanical device such a lever , spring and a mass and were often energied by compressed air. !he first PID controller was developed by "lmer #perry in $%$$ and theoretical analysis first introduced by &ussian 'merican engineer (icolas )inorsky, *)inorsky $%++. !he goal is stability, not general control, which simplified the problem significantly. Proportional control provides stability against small disturbances while derivative term was added to improve stability and control. In modern years, PID controllers in industry are implemented in programmable logic controllers *P-s and applied in industrial ovens, plastics in/ection machinery, hot stamping machines . It used the the implementation of the PID algorithm. 40 48

PID controller theory an e!"ation

4%

1

12

+

τ i ( s) s

+ τ  ( ) d s

G c ( PID ) = K c ¿



1$

3here

 K c

 is the PID control gain,

τ i ( s)

 is the integral gain,

τ d ( s )

 is the derivative

gain 1+ 5#

Pro$ortional Action

14

Proportional *P control has a function in determining the magnitude of the

difference between the set point and the process variable which is indicated as error. !hen this  proportional control will applies appropriate proportional changes to the control variable to eliminate error. )any control systems will, in fact, work uite well with only Proportional control due to it fast response time and its ability to minimie fluctuation. 5owever, it contains large offset. It is an instantaneous response to the control error for improving the response of a stable system. ontrastly, it cannot control an unstable system by itself. !herefore when the freuencies leaving the system , the gain is the same with a nonero steadystate error. 55

Inte%ral Action

16

Integral *I control usually e7amines the offset of set point and the process

variable over time and corrects it when and if necessary. !his integral control has small offset and always return to steady state but it leads to slow response time. Integral action drives the steadystate error towards 2 but slows the response since the error must accumulate before a significant response is output from the controler. #ince an integrator introduces a system pole at the origin, an integrator can be detrimental to loop stability. 8nly controllers with integrators can windup where, through actuator saturation, the loop is unable to comply with the control command and the error builds until the situation is corrected. 10 58

Deri&ati&e Action

1%

Derivative *D control, monitored the rate of change of the process variable and

conseuently makes

changes

to

the

output

variable

to

provide

unusual

changes.

3hen there is a 9process upset9, meaning, when the process variable or the set point uickly changes  the PID controller has to uickly change the output to get the process variable back  eual to the set point. 8nce the PID controller has the process variable eual to the set point, a good PID controller will not vary the output. !hus, there are two responses occur such as fast

response *fast change in output when there is a 9process upset9, but slow response *steady output.

62 '1

Controller %ain

6+

!he proportional gain *: c determines the ratio of output response to the error 

signal. ;or instance, if the error term has a magnitude of $2, a proportional gain of 1 would  produce a proportional response of 12. In general, increasing the proportional gain will increase the speed of the control system response. 5owever, if the proportional gain is too large, the  process variable will begin to oscillate. If : c is increased further, the oscillations will become larger and the system will become unstable and may even oscillate out of control. '#

Deati(e

64

Deadtime is a delay between when a process variable changes, and when that

change can be observed. ;or instance, if a temperature sensor is placed far away from a cold water fluid inlet valve, it will not measure a change in temperature immediately if the valve is opened or closed. Deadtime can also be caused by a system or output actuator that is slow to respond to the control command, for instance, a valve that is slow to open or close. ' common source of deadtime in chemical plants is the delay caused by the flow of fluid through pipes. '5

Effect of increasin% an ecreasin% &al"e of P)I *D to+ar $rocess res$onse

66

3hen parameters of an e7isting controller have to be tuned, there will be a

 problem in the identification of PID controller. ontroller structure has to be determined since manufacturers do not provide data on controller structure whether serial or parallel. )anual tuning of controller parameters had to be done if they are changed with time. 8ther than that, manual tuning of controller parameters also had to be done when change in process parameters occurred. )anual parameter tuning can be done using trial and error and if rules shown in the table below< 67 71

P!"!e.e" Increasing K

68

S3ee 4  

Re$34$e 72 Increases

69 73

S.!*.+

70

A"!+

Deteriorate

74

Improves

75

79

Increasing Ki Increasing K d

76 80

Decreases increases

77 81

Deteriorate Improves

78 82

Improves No effect

=> =4 =1

,ettlin% ti(e < !he time at which the P? reaches @ 1A of the total change in the

=6 =0

O&ershoot

process variable *BP?. < )ost notably associated with Ponly controllers, is the difference fromthe

#P to == =%

Decay ratio

where the P? settles out at a steady state value. <

!he sie of the second peak above the new steady state divided by thesie of the %2

first peak above the same steady state level

-1

%+

8b/ective of this study is to determine the effect of PIDCs parameters

to the process controllability. !o study the effect of controller gain, effect of integral time, effect of derivative time and effect of deadtime on the control loop process. %> %4 %1 %6 %0 %= %% $22

$2$ $2+ $2> $24 1.5

CHAPTER / : 0ETHODOO23

106

LA/ 1% Ee. 4 C4."4e" G! .4 P"4e$$ C4."4!*.+

107

P"4e"e

$

8pen matlab software then new model is opened by selecting file button.

+

!hen, untitled window will appear.

> lick button simulink library browser, then drag clock, to workspace, constant, PID controller, $2= order.

transfer fcn , sum, scope and display. 'rrange and connected all simulink in the right

1 s  s

+

+ $2 s

4

Process transfer function is set as

1

PID controllerEs parameter was setup as P$2.21, I$2.2$, D$2

6

#et simulation parameters to 622

0

&un the simulation

=

Plot P? vs time

$2%

, process set point$

FFplot*time,P?

%

&un a second set of PIDEs value P+2.$, I+2.2$, D+2

$2

Plot the second process response

$$2

FFfigure*+,plot*time,P?

$$

&un a third set of PIDEs value P>2.+, I>2.2$, D>2

$+

Plot the third process response

$$$

FFfigure*>,plot*time,P?

$>

?iew all the figure in figure palette.

$4

ombine response of figure*+ and figure*> into figure*$

$1

&ename the 7a7is as time and ya7is as P? and every figure as PID$, PID+, and PID>.

$6

#how the #P at $.

112 113

114

115

Figure 1 : PFD FOR EFFECT OF CONTROLLER GAIN

116

117

LA/ 2% Ee. 4 I.e:"! G! .4 P"4e$$ C4."4!*.+

118

P"4e"e

$

8pen mat lab software then new model is opened by selecting file button.

+

!hen, untitled window will appear.

$$% >. lick button simulink library browser, then drag clock, to workspace, constant, PID controller, transfer fcn, sum, scope and display. 'rrange and connected all simulink in the right order. 1 s  s

$+2

4. Process transfer function is set as

+

+ $2 s

, process set point$

$+$

1. PID controllerEs parameter was setup as P$2.21,I$2.2$,D$2

$++

6. #et simulation parameters to 622

$+>

0. &un the simulation

$+4

=. Plot P? vs time

$+1

FFplot*time,P?

$+6

%. &un a second set of PIDEs value P+2.21 I+2.2+ D+2

$+0

$2. Plot the second process response

$+=

FFfigure*+,plot*time,P?

$+%

$$. &un a third set of PIDEs value P>2.21 I> 2.24, D>2

$>2

$+. Plot the third process response

$>$

FFfigure*>,plot*time,P?

$>+

$>. ?iew the figure in figure palette

$>>

$4. ombine response of figure *+ and figure *> into figure *$

$>4

$1. &ename the 7a7is as time and ya7is as P? and every figure as PID$, PID+, PID>.

$>1

$6. #how the #P at $.

$>6

137

1#8

Figure 2 : PFD for integral gain

$>% $42

11 12 1& 1 15 16

LA/ &% Ee. 4 ,e";.;e .e .4 P"4e$$ C4."4!*.+

17

P"4e"e

$4=

$. 8pen )at lab software then new model is opened by selecting file button. $4%

!hen, untitled window will appear.

$12 >. lick button simulink library browser, then drag clock, to workspace, constant, PID controller, transfer fcn , sum, scope and display. 'rrange and connected all simulink in the right order. 1 s  s

+

+ $2 s

$1$

4. Process transfer function is set as

, process set point$

$1+

1. PID controllerEs parameter was setup as P$2.21,I$2.2$,D$2

$1>

6. #et simulation parameters to 622

$14

0. &un the simulation

$11

=. Plot P? vs time

$16

FFplot*time,P?

$10

%. &un a second set of PIDEs value P+2.21 I+,2.2$ D++

$1=

$2. Plot the second process response

$1%

FFfigure*+,plot*time,P?

$62

$$. &un a third set of PIDEs value P>2.21 I>2.2$, D>4

$6$

$+. Plot the third process response

$6+

FFfigure*>,plot*time,P?

$6>

$>. ?iew the figure in figure palette.

$64

$4. ombine response of figure *+ and figure *> into figure*$

$61

$1. &ename the 7a7is as time and ya7is as P? and every figure as PID$, PID+, PID>.

$66

$6. #how the #P at $.

$60 $6=

169 170

171

172

Figure 3 : PFD for eri!iti!e ti"e

17& 17

LA/ % Ee. 4 e!.e .4 P"4e$$ C4."4!*.+

175

P"4e"e

$06

$. 8pen mat lab software then new model is opened by selecting file button.

$00

+. !hen, untitled window will appear.

$0= >. lick button simulink library browser, then drag clock, to workspace, constant, PID controller, transfer fcn , variable time delay , sum, scope and display. 'rrange and connected all simulink in the right order.

1 s  s

$0% 4. Process transfer function is set as and set $=2

+

+ $2 s

, process set point$. 'dd Gtransport delayH

!ime Delay to 1.

$=$

1. PID controllerEs parameter was setup as P$2.+, I$2.2$,D$2

$=+

6. #et simulation parameters to 622

$=>

0. &un the simulation

$=4

=. Plot P? versus time

$=1

FFplot*time,P?

$=6

%. &un a second set of !ime delay  0

$=0 $== $=%

$2. Plot the second process response FFfigure*+,plot *time,P?

$%2

$$. &un a third set of !ime delay  %

$%$

$+. Plot the third process response

$%+

FFfigure*>,plot *time,P?

$%>

$>. ?iew the figure in figure palette.

$%4

$4. ombine response of figure *+ and figure *> into figure *$

$%1

$1. &ename the 7a7is as time and ya7is as P? and every figure as PID$, PID+, PID>.

$%6

$6. #how the #P at $.

197

198

1##

Figure $ : PFD for eati"e

200 201 202 20&

CHAPTER & % RESULT AN, ,ISCUSSION

20

LA/ 1% Ee. 4 C4."4e" G! .4 P"4e$$ C4."4!*.+

205

Re$.

206

1 . 8 PI D1 1 . 6 PI D2

1 . 4 PI D3 1 . 2

SP 1       V       P

0 . 8

0 . 6

0 . 4

0 . 2

0 0

1 0 0

2 0 0

3 0 0

4 0 0

5 0 0

6 0 0

t i me

2%7

Figure 5 : Co"&ination of 3 gra'( )ontroller gain

/.8

DI,,CU,,ION

+2%

In the figure above shows > different graph plotted in order to observe the oscillations of 

each graph plotted. !he > different values of Proportional *P are considered which are 2.21, 2.$, and 2.+. ased on the graph, it can be concluded that the high proportional value will lead the system to become unstable and oscillate. !he proportionality is given by controller gain. ;or a given change in time, the amount of output process value *P? will be determined by the controller gain. It is the best controller gain if the peak of the graph reaches the set point. ;rom the graph obtained, figure > has the best controller gain since the peak point of the graph is nearest to the set point *#P$. !hatCs why this condition will contribute to better processes.

210 211

212

LA/ 2% Ee. 4 I.e:"! G! .4 P"4e$$ C4."4!*.+

21&

Re$.

214

1 . 8 PI D3 PI D2 1 . 6 PI D1

1 . 4

1 . 2

SP 1       V       P

0 . 8

0 . 6

0 . 4

0 . 2

0 0

1 0 0

2 0 0

3 0 0

4 0 0

5 0 0

T I ME

215

Figure * : Co"&ination of 3 gra'( Integral ti"e

216 /1

DI,,CU,,ION

+$=

;or second e7periment is to find the effect of integral time. !he larger value of integral

time, the more oscillates of the graph obtained. ased on observation of the graph, there are more oscillations for integral time, I2.24. !hus, the integration will take part until the area under the curve becomes ero. If there is decreasing in I, it will result in instability system. ;rom the graph, it can be concluded that increasing too much I will contribute the present value to overshoot the set point value. ;igure 6 has a better process since the peak point reaches nearest to

the set point. #o that, we can conclude that the increasing value of I will lead the graph to more oscillations.

219

LA/ &% Ee. 4 ,e";!.;e Te .4 P"4e$$ C4."4!*.+

220 221

1 . 8

1 . 6

PI D1 PI D2

1 . 4 PI D3 1 . 2

SP

1       V       P

0 . 8

0 . 6

0 . 4

0 . 2

0 0

1 0 0

2 0 0

3 0 0

4 0 0

5 0 0

6 0 0

T I ME

///

Figure 7 : Co"&ination of 3 gra'( Deri!ati!e ti"e

++> //4

DI,,CU,,ION:

++1

;rom the the graph obtained, it can be concluded that the larger values of derivative will

decrease the overshoot. esides that, this change will lead to instability since it will slow down

transient response. In fact, derivative control is used to reduce the magnitude of the overshoot  produced. Derivatives term is also used in slow processes such as processes with long time constant. ++6 227 228 229 230

2&1

LA/ % Ee. O ,e!.e .4 P"4e$$ C4."4!*.+

2&2

Re$.

233

2 . 5

PI D3 2

PI D2 PI D1 1 . 5

      V       P

SP 1

0 . 5

0 0

1 0 0

2 0 0

3 0 0

4 0 0

5 0 0

T i me

234 235

Figure + : Co"&ination of 3 Gra'(, for Di-erent eati"e

6 0 0

/#'

DI,,CU,,ION

+>0

ased on the graphs, it can be concluded that the increasing in !ime Delay will produce

more oscillations on the graph. !he calculation is starting at the dead time icon. !he more time delay, the instability of the system also increases. !his is due to the long stopped reaction time. ;or time delay  1, there is not much oscillation occur. 3hen we increase the time delay to 0, there is small oscillation occur. 238 239 240 241 242

/4#

CHAPTER 4 : CONCU,ION AND RECO00ENDATION

+44 +41

!he performance of each of the three types of controllers varies due to the differing

components of controller euation. In Ponly control, the only ad/ustable tuning parameter is :  as the proportional term is the only term in the corresponding controller euation. !he advantage of  Ponly control is that there is only one tuning parameter to ad/ust and therefore the best tuning values are obtained rather uickly.!the disadvantage to Ponly control is that it permits offset. !o minimie offset, :  may be increased, however this results in greater oscillatory behavior. +46

!he advantage to PI control is that it eliminates the offset present in Ponly control

 by minimiing the integrated area of error over time. !o assess the effect changing the two tuning  parameters has on a PI controller performance, both :  and JI were halved and doubled. In this  process, using these tuning parameters actually resulted in increased magnitude of oscillations over  time and thus an unstable system. "ither lowering JI, or increasing :   from the initial value resulted in a greater peak overshoot, larger settling time and larger decay ratio. +40

In PID control all three terms are utilied. !he function of the derivative term is to

determine the rate of change of the error *slope thus influence the controller output. ' rapidly changing error will have a larger derivative and therefore a larger effect on controller output. !he derivative term will therefore work to decrease the oscillatory behavior in the process variable. !o

assess the effect of changing derivative time, a comparison of the tuning parameter JD was made for the PID controller by halving and doubling the initial value. +4=

Increasing the derivative time results in less oscillatory behavior of the process

variable however there is also an increased noise in the controller output. Increasing JD  also increase rise time, settling time, and decreases peak overshoot +4% +12 +1$ +1+ +1> /54

RECO00ENDATION /55

In choosing the KbestC performing controller it must be noted that best

 performance is sub/ective, meaning that some processes may desire a P? response with no overshoot, others may be able to tolerate overshoot and prefer faster rise times. ;or a process that desires fast rise time with the minimal amount of oscillatory behavior and overshoot it would be suggested to use a moderate to moderately aggressive PI controller. 256 257

/58

RERENCE,

1. 'bdul 'i Ishak L Maliawati 'bdullah. *+2$4. PID !N(I(O  Fundamental Concepts +1%

and Application. NI!) Press.

2. 5. ischoff, D.5offmann, ".?.!eri. *$%%0. Process ontrol #ystem, Control of  260

Temperature, Flow and Filling Level. ;esto Didactic Omb5 L o.

>. asso, hristophe *+2$+. 9Designing ontrol -oops for -inear and #witching Power  +6$

#upplies< ' !utorial Ouide9. 'rtech 5ouse, I#( %0=$62=201100

+6+ 4. lanke, ).Q :innaert, ).Q -une, R.Q #taroswiecki, ). *+226, iagnosis and +6> +64 +61 266

 Fault!Tolerant Control  *+nd ed., #pringer