1. Priyatmadi Jurusan teknik Elektro FT UGM
Pengendalian Proses
Priyatmadi
Jurusan teknik Elektro
FT UGM
Process Control
Priyatmadi 2008

2. ARITHMETIC VERSUS LOGIC CONTROL
EXAMPLE OF ARITHMETIC CONTROL
PID control, fuzzy control, adaptive control etc
EXAMPLE OF LOGIC CONTROL
Start-stop motor, sequential control, emergency shut down system
COMBINATION OF ANALOG AND LOGIC CONTROL
Process Control
Priyatmadi 2008

3. Arithmetic Control - + Cold water in steam in hot water out 3-15psi
Set point TT
I/P
TIC
4-20 mA
4-20 mA
c(t)
Set point +
e(t)
m(t)
Controller
Plant -
Sensor
Process Control
Priyatmadi 2008

4. CONTROL ACTION + How to compute m(t) Controller e(t) m(t) ON-OFF
PROPORTIONAL (P)
PROPORTIONAL + INTEGRAL (PI)
PROPORTIONAL + DIFFERENTIAL (PD)
PID
AUCTIONEERING
RATIO CONTROL
MODERN CONTROL +
Process Control
Priyatmadi 2008

5. ON-OFF CONTROL ACTION - m(t) = M1 if e(t)>0 m(t) = M2 if e(t)<0
Plant
Controller
Sensor + -
Set point
r(t)
m(t)
e(t)
c(t) e m M1 M2
m(t) = M1 if e(t)>0
m(t) = M2 if e(t)<0
Process Control
Priyatmadi 2008

6. ON-OFF CONTROL ACTION WITH GAP
Set point
r(t)
c(t) +
e(t)
Controller
m(t)
Plant -
c(t)
Sensor m e M1 M2
m(t) = M1 if e(t)>e1
m(t) = M2 if e(t)<e2 e2 e1
Process Control
Priyatmadi 2008

7. Example of ON-OFF action
h(t)
qi(t)
qo(t)
Level sensor
Process Control
Priyatmadi 2008

8. example
Process Control
Priyatmadi 2008

9. Proportional Control Action
Set point
r(t)
e(t)
c(t) +
m(t)
Controller
Plant -
c(t)
Sensor
e(t)
m(t) t
m(t)=Kpe(t)
Process Control
Priyatmadi 2008

10. Integral Control Action
Plant
Controller
Sensor + -
Set point
r(t)
m(t)
e(t)
c(t)
m(t)=Ki∫e(t)dt
m(t)
e(t) t
Process Control
Priyatmadi 2008

11. Derivative Control Action
Plant
Controller
Sensor + -
Set point
r(t)
m(t)
e(t)
c(t)
m(t)=Kd(de(t)/dt)
m(t)
e(t) t
Process Control
Priyatmadi 2008

12. Problem in Analog control
Stability
Sensitivity
Disturbance rejection
Steady state accuracy
Transient response
Noise
Process Control
Priyatmadi 2008

13. STABILITY
A control loop will be stable if at the frequency of oscillation that gives a total phase shift of 3600 around the loop, the gain around the loop is less then 1
Plant
Controller
Sensor + -
Set point
r(t)
m(t)
e(t)
c(t)
Process Control
Priyatmadi 2008

14. OUTPUT OF CONTROL SYSTEM WHEN SET POINT IS RISEN
Plant
Controller
Sensor + -
Set point
r(t)
m(t)
e(t)
c(t)
n t
c(t)
UNSTABLE
r(t)
Process Control
Priyatmadi 2008

15. SENSITIVITY
Sensitivity is a measure of changes in system characteristic due to changes in parameters.
Example:
Load change
Sensor characteristic change
Plant characteristic change etc.
Controller can be design to be insensitive to one parameter but often it must be sensitive to the others.
Process Control
Priyatmadi 2008

16. Disturbance rejection
The input to the plant we manipulated is m(t). Plant also receives disturbance input that we do not control. The plant then can be modeled as follow
D(t)
M(t) +
C(t)
Gp(t)
Gd(s)
plant Gc – H
Gd(t)D(t)
R(r)
Methods to reduce Td(j)
make Gd(s) small
increase loop gain by increasing Gc
reduced D(s)
use feed forward compensation
Process Control
Priyatmadi 2008

17. Disturbance rejection
Feedforward compensation
Feedforward compensation can be applied if the disturbance can be measured.
C(s)
D(s)
M(s) +
Gp(s)
Gd(s)
plant Gc – H
Gd(s)D(s)
Gcd(s)
R(s)
Process Control
Priyatmadi 2008

18. 5.5 Steady State Accuracy ess R(t) C(t)
n t
c(t)
R(t)
C(t)
M(t)
Gp(t) Gc + –
R(t)
E(t)
ess
C(t)
Used integrator to eliminate steady state error but be carefull system can be unstable
n t
c(t)
r(t)
Process Control
Priyatmadi 2008

19. Time Response of Control System
The typical of unit step response of a system is as
nt
c(t)
Mpt
1.0
0.9
0.1 Tr Tp
1+ d
1 d
css Ts
Process Control
Priyatmadi 2008

20. Problem of Noise
Random, meaningless signals can occur in many parts of control loops. These signals, often referred to as noise, can interfere with the intelligence of the signal.
For example, heater control the cold water and heated water may not be completely intermixed by the time they reach the thermometer bulb. Slugs of cold water may alternate with hot water to give a rapidly fluctuating, wholly meaningless temperature signal at the bulb.
If such a noise bearing signal is allowed to reach the controller, it may result in wild and meaningless corrections to the process, which may cause fluctuating or completely unstable automatic control.
Process Control
Priyatmadi 2008

21. Problem of Noise
Similar noise problems can occur in connection with most signals, e.g.,
random pulsations in pressure signals,
waves in liquid-level signals,
turbulence in differential-measured flow signals, and
induced currents in circuits (electromagnetic wave, lightning, groundloop, etc)
Process Control
Priyatmadi 2008

22. Solutions to Noise Problem
Derivative action produces difficulties where noise exists and, therefore, it should generally not be used in such instances.
Filtering or averaging the noise out of the signal. For example, in heater control the source of the thermal noise can be eliminated by better mixing of the hot and cold water in the tank or by using an averaging-type thermometer bulb that measures temperature over a considerable length instead of at one point.
Process Control
Priyatmadi 2008

23. Solutions to Noise Problem
Reduction or elimination of the noise at its source, for example
rotary instead of reciprocating pumps to avoid pulsating pressures,
larger mixing tanks or surge tanks,
stirrers to obtain a uniform signal,
longer pipe runs and straightening vanes in flow measurement,
shielding of wires against stray voltages
Use STP wires.
Process Control
Priyatmadi 2008

24. Ratio Control
In ratio control, a predetermined ratio is maintained between two or more variables.
Each controller has its own measured variable and output to a separate final control element.
However, all set points are from a master primary signal that is modified by individual ratio settings
A typical application of ratio control is the control of the fuel flow/airflow ratio in a combustion control system
Process Control
Priyatmadi 2008

25. Process Control
Priyatmadi 2008

26. Auctioneering Control (Override Control, Limiting Control)
In suction and discharge pressure compressor control, the discharge control valve is normally regulated from the discharge pressure.
However, if the suction pressure drops below its set point, control is transferred to the suction pressure controller.
This prevents excessive suction on the supply side, from demand exceeding supply, with resultant compressor damage
Process Control
Priyatmadi 2008

27. Auctioneering Control (Override Control, Limiting Control)
Process Control
Priyatmadi 2008

28. Modern Control Action Fuzzy control Optimal control
Sliding mode control
Adaptive control (Self tuning control)
Process Control
Priyatmadi 2008