Process Control System


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A PCR is an acronym for the ‘Process Control Rig' .Its a typical illustration of the industrial process in which temperature, process fluid level and the flow rate can be controlled. It's a typical industrial system used in the petrochemical and food processing industries.

The process control rig makes use of the sump, pump, the process tank and the overflow for a fluid cycle. The sump stores the fluid which is then driven through the system; the pump lets the fluid pass into the process. The process tank ensures that there is even distribution of temperature in the tank by making use of its immersion heating element and a stirrer. This process goes around again when the fluid is drained through the overflow manual drain valve.

The PCR can be controlled either manually or by using the computer.


The experiment is performed for a given complete cycle around the process control rig using a manual control.

Procedures (Manual Control)

  • The slider control was used to pump the fluid around the system.
  • The fluid was diverted through the cooler, the effect was observed.
  • The cooler was switched ON and OFF, the effect was observed.
  • The stirrer was also switched ON and OFF.
  • The flow rate was varied using the gate valve, the effect was observed on the pump and the meter reading.
  • The process tank was filled until it is full and stopped when it overflows.
  • Using the heat output slider, the fluid was heated to 50˚C.
  • The temperature was later reduced by draining the fluid back into the sump.


Following all the above procedures, the PCR behaved exactly as I wanted it to using all the controls as stated in the procedures.

Procedures (Computer Control)

  • The computer control was used and ‘Flow Control' was selected.
  • The Set Point was set to 0.81/min.
  • The Sample Time was set to 0.05s.
  • Then P = 1: D = 0.2 : I = 0.5
  • The ‘Start' button was clicked and the transient response was printed.


PID controllers are used to control the flow cycle by using the PID control element using the computer. PCI controllers are also widely used in the industry like the PCR that was earlier experimented. PID controllers could be hydraulic, electric, and electronic and are implemented through the use of microprocessors. This experiment will be used to investigate the effect of P, I and D (Proportion, Integral and Derivative).


Investigating Proportional Gain using Flow Control


  • The flow control is selected in the preference box of the interactive software.
  • The desired flow rate is set and the sample time is set to 0.05 seconds.
  • A set input is applied.
  • The IAT = 0, DAT = 0, and proportional gain (PG) = 0.5.
  • Start the process and tune the proportional control from 0.5 - 10.



Measured Value

Steady State Error



1 - 0.13 = 87%



1 - 0.31 = 69%



1 - 0.47 = 53%



1 - 0.52 = 48%



1 - 0.59 = 41%



1 - 0.63 = 37%



1 - 0.67 = 33%



1 - 0.70 = 30%



1 - 0.75 = 25%



1 - 0.90 = 10%

Analysing the table of results, as the gain is increased the measured value of the of the system and the steady state error decreased from the 0.5 - 10 PG range .It can be said about the system that when the gain is set to high the measured value remained the same and any increase in the PG value would not make any difference. Also at high gain, the system becomes a bit unstable and the offset is very high. The use of proportional gain is not only used to produce adequate control but also to measure the stability and the offset in this system, also it could be used to relate stability to the level of disturbance encountered when diversion of fluid takes place.

Large proportional gain leads to an unstable system and a small proportional gain leads to a less responsive controller system.


Proportional gain plus Integral (PI ) Control of Flow-Rate


  • A gain that provides stable proportional offset is chosen.
  • A set input is applied.
  • A load change is introduced by diverting the fluid through the cooler using the manual divert valve.


SP = 1 PG = 1 DAT = 0 Sample time = 0.05



Overshoot (%)

Setting Time (s)

Rise Time (s)


Critical damped





Critical damped





Critical damped





Under damped





Under damped





Under damped





Over damped





Over damped





Over damped





Over damped




The transient graph of the system response with respect to time is on the next stage. The transient graph reflects an over damped condition with a settling time of around 5.8s.The system is in a stable state.

Analysing the table of result, the sine wave generated was critically damped for IAT (0.1 - 0.3), it was under damped when IAT (0.6 - 1.0) and over damped as the IAT (Integral Action Time) value increases to 10.0.The overshoot was much until when IAT = 2.0 when there was no overshoot recorded in the system, at this stage the system is more stable. Also as IAT gets higher, the settling time and the time taken for the wave to rise increases.

IAT is used in this system because integral control removes steady state that arises when using only proportional controller by accelerating the systems process towards a given set point value.


Proportional plus Derivative (PD) Control of Flow-Rate


  • The same proportional gain (1) used in experiment 2 is used.
  • The IAT is set to zero.
  • The sample time is set to 0.05 seconds.
  • A set input is applied.
  • The DAT is varied through 0.1, 0.3, and 0.6.

A transient response of the system response with respect to time is on the next page. Analysing the graph;

When DAT = 0.1

The response represents an under damped situation. The response also has a long settling time. There was no overshot and the response shows that the system is not stable.

When DAT = 0.3

The response represents a damped situation (in between over damped and under damped). The response also has a short settling time .There was a bit of over shoot at the start but late settles and reached a steady state (15.1s).The system at this stage is more stable than when DAT is 0.1.

When DAT = 0.6

The transient response generated when DAT = 0.6 is very over damped. The response shows that the system is very unstable at this stage and the system didn't look like it would settle for a long time, the settling time would therefore be longer than when DAT = 0.1 and 0.3.

Therefore, increasing the DAT (Derivative Action Time) any longer will cause the system to be more unstable and a longer settling time.


Proportional, Integral plus Derivative (PID) Control of Flow-Rate


  • The same proportional gain (PG = 1) is used.
  • The IAT is set to zero.
  • The sample time is set to 0.05 seconds.
  • A set input is applied.
  • The DAT is varied through 0.1, 0.2, and 0.3.

A transient response of the system response with respect to time is on the next page. Analysing the graph;

When DAT = 0.1

The transient response shows the rise time to be around 4.2s.The response is over damped and settles at around 14.5s.Its a bit unstable.

When DAT = 0.2

The transient response is also over damped like when DAT = 0.1.The rise time is about 7.2s. The response settles at around 12.3s. The system at this stage is more stable and settling time is smaller than when DAT = 0.1.

When DAT = 0.3

When DAT = 0.3, the transient response shows the rise time to around 4.5s.The settling time for the response is around 15.3s.The system is stable as well. Comparing this stage of the system with when DAT = 0.1 and 0.2, it is more stable and the trend is that as DAT increases, the settling time increases.

Effect of combining all three elements together

If the attached graphs are been analysed, the addition of Integral control to the proportional control helped to eliminate the proportional effects from the proportional controller. Also adding the derivative controller to the proportional controller helps to reduce the peak offset experienced from the reduced loop offset. The derivative controller also eliminates the overshoot generated with the integral controller. The choice of any of these elements depends on the characteristics of the given system or process.

The effects of each element P, I and D

Effect of Proportional control

The proportional control is described by its proportional offset. The proportional offset of a system is the difference between the set point (what you want) and the measured value (what you are expecting).Tuning a proportional control system would affects its performance, but a best performance would be observed if the proportional control is tuned to the system in operation. The larger the proportional offset, the greater the correction needed to the output. The proportional control affects the stability of the process as it helps to determine the throttling range for the system stability and eliminates too large offsets and errors.

Effect of Integral control

The function of an integral control is to generate an output based upon the error history of a given system. It gets rid of the proportional offset over time by adjusting the controls output. Adding an integral control to a proportional control could make the system unstable, so to make the system stable an adjustment to reduce the proportional gain of the system needs to be made. Its major effect to the process is to eliminate the proportional effects in the process or system.

Effect of Derivative control

This is a control that works on the basis of the rate of change of error multiplied by the derivative time constant. It takes into consideration that it takes time for the input to reflect a change at the output. It is also useful in minimising swings seen in a system as a result of load change. In comparison to the other two controls, it cannot be used alone as there won't be any zero rate of change at the controller output. It effect in a process is to reduce the response time of the system.

An unreasonable choice of value for a derivative control would make the system unstable. Also if the derivative control is set correctly, it gives stability and allowance to determine the P and I constants more aggressively to give high performance.

Computer controlled response

It involves the use of software tools which could be costly and would need some training. It allows for consistent tuning, enables the use of valves and sensors analysis is allowed. It also helps to simulate the system before downloading.

Manually controlled response

It is a contrast to the computer controlled response as it requires someone who is experienced to operate the system. Its tuning might not be as consistent and precise as the computer controlled system.


The use of PID controller is important in process control in other to balance the response (output) with the set point. Good PID controllers would not vary the output but keep the output steady. For example, if the valve or any control element changes constantly (not keeping a constant value), a lot of wear would be caused on the control elements in the process. Also in improving the performance of process control, it is advisable to start with choosing small values for P.I and D constants and increases it later to improve the stability but doing otherwise would make the process control very unstable.

Since the proportional offset is reduced in process control using PID controllers, this helps to save energy and cost by making the system more consistent and precise. PID controllers also have its limitations. For example, PID controllers are linear and therefore needs some enhancement to operate in non-linear systems. But overall, a good and appropriate use of PID controllers in process control would bring stability and consistency to the system.

REFERENCES [last accessed 21/03/08]

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