College of Applied Sciences –Sohar Course Name: process dynamic and control Course Code: CHEN4352
Experiment name and Number 2-THE EFFECT OF PI AND PID CONTROLLERS ON FLOW CONTROL SYSTEM
T Abstract:-1 1
his experiment was performed to study the effect of PI and PID controllers on flow control system. A( PCT-100 ) device was used in this experiment. In any automation process, controllers are required, to control some of the parameter such as temperature, pressure, flow rate, level etc. The difference between the reference signal and the feedback signal is error signal. The error signal drives a control valve or a damper to control, the process variables like tank level, fluid flow, pressure or temperature to the set point. P-I controller is mainly used to eliminate the steady state error resulting from P controller. However, in terms of the speed of the response and overall stability of the system, it has a negative impact. This controller is mostly used in areas where speed of the system is not an issue. Since P-I controller has no ability to predict the future errors of the system it cannot decrease the rise time and eliminate the oscillations. If applied, any amount of I guarantees set point overshoot. P-I-D controller has the optimum control dynamics including zero steady state error, fast response, no oscillations and higher stability. The necessity of using a derivative gain component in addition to the PI controller is to eliminate the overshoot and the oscillations occurring in the output response of the system. One of the main advantages of the P-I-D controller is that it can be used with higher order processes including more than single energy storage.
2- Table of content: 2
Table of content:
page
Table of content
3
Objective Introduction Equipment Method and experiment procedure
4 4 5 6
Results Discussion
7 15
Conclusion
15
References
16
List of tables: PI controller PID controller
Table 7.1 Table 7.2
List of figures: Figure 5.1
The Device PCT-100 includes the following elements
Figure 7.1
Graph of flow rate vs time
Figure 7.2
Graph of flow rate vs time
Figure 7.3
Graph of flow rate vs time
Figure 7.4 Figure 7.5 Figure 7.6 Figure 7.7 Figure 7.8 Figure 7.9 Figure 7.10 Figure 7.11 Figure 7.12 Figure 7.13
Graph of flow rate vs time Graph of flow rate vs time Graph of flow rate vs time Graph of flow rate vs time Graph of flow rate vs time Graph of flow rate vs time Graph of flow rate vs time Graph of flow rate vs time Graph of flow rate vs time Graph of flow rate vs time
3-Objectives: 3
To study the effect of PI and PID controllers on flow control system.
4-Introduction: The controller (an analogue/digital circuit, and software), is trying to keep the controlled variable such as temperature, liquid level, motor velocity, robot joint angle, at a certain value called the set point (SP). A feedback control system does this by looking at the error (E) signal, which is the difference between where the controlled variable called the process variable (PV) is, and where it should be. Based upon the error signal, the controller decides the magnitude and the direction of the signal to the actuator. The proportional (P), the integral (I), and the derivative (D), are all basic controllers. Types of controllers: P, I, D, PI, PD, and PID controllers PI-controller: it includes two control actions (1) proportional and (2) integral, this integral action eliminates the offset, order increases, if the order increases, then the overall response will be sluggish, To speed up the process, either kc (PG) value has to be increased or integral (Ʈi) value has to be decreased, but if the kc value is sufficiently large or (Ʈi) value is sufficiently small then instability problem will arise. On the other hand PIDcontroller: it includes three control actions, proportional, integral and derivative. It eliminates the offset because of integral action, the addition of derivative action improves the stability of the process, and if the error is constant then no derivative action is required. For a noisy response with almost zero error, the derivative term leads to large control action although that is not required.
The performance of the control systems is determined by the nature of the process, the characteristics of the controller, the location and magnitude of the disturbance. Sometimes the performance of feedback control system will be unsatisfactory because of large uncontrolled load changes, hence other control schemes can be considered. The best way of using an additional controller to decrease upsets is to use the scheme called cascade control.
4
5-Equipment: A PCT-100, Process Control Technology model is a bench-top system which implements several continuous fluid processes. The main elements of the PCT-100 are the process rig and control module. The rig includes the following elements: sump, pump, turbine flow meter, process tank, sensor for level, vent pipe, needle drain valve, proportional drain valve, pressure transducer, float switch, check valve, forced air cooler and proportional valve.
1. Process tank
2. Sump tank
3. Cooler Unit
4. Sump tank Temperature sensor (PRT)
6. 3/2 Diverter valve
7. 2/2 Proportional control valve
5. Variable speed pump with filter and pressure switch 8. Flow rate sensor
10. 2/2 Proportional drain valve
11. Needle valve
12. Pressure relief valve
13. Heater
14. Level sensor
15. Pressure transducer
16. Float switch
17. Overflow/Vent valve
18. Digital LCD displays
9. One way check valve
19. Indicator lights
Figure 5.1: The Device PCT-100 includes the following elements
5
6-Method and experiment procedure: PI Controller 1. Ensuring that the vent valve at the top of the process tank was opened. 2. The menu flow controller was clicked. 3. Set Point (SP) was kept as constant value of (2). 4. steady state input signal was set. 5. The Proportion Gain (PG) value was kept constant as (1). 6. The flow loop experiment was started with addition of an element of integral (I) action after about ten seconds. 7. The set up was started and the necessary arrangements ware done to operate the control system through computer system. 8. This process was repeated several times and each time increased the amount of integral action (I). 9. The final steady state flow value was recorded (if the flow actually did settle) and main observations as to the nature of the response also recorded.
PID Controller 10. The instructions (1-5) were followed and derivative (D) was included the effect of derivative action was investigated by run a flow experiment with SP= 1, PG=1 and vary the I and D values. 11. The observations were inference. 12. The response was studied, the steady state values were recorded and observations were commented.
6
7-Results:
*Calculate Experimental offset by graph the different between flow rate and time. *Theoretical offset
=
SP 1+PG
*Error Percent difference =
│𝐸𝑥𝑝𝑒𝑟𝑖𝑚𝑒𝑛𝑡𝑎𝑙 𝑣𝑎𝑙𝑢𝑒−𝑇ℎ𝑒𝑜𝑟𝑖𝑡𝑖𝑐𝑎𝑙 𝑣𝑎𝑙𝑢𝑒 │ 𝑇ℎ𝑒𝑜𝑟𝑖𝑡𝑖𝑐𝑎𝑙 𝑣𝑎𝑙𝑢𝑒
* 100%.
Part 1: PI Controller.
Table 7.1: PI controller
No
SP
PG
I
1 2 3 4 5 6
2 2 2 2 2 2
1 1 1 1 1 1
999 500 10 0.5 0.2 0.1
Steady Theorrtical Experimental state offset offset 1.17 1 0.83 1.2 1 8 1.92 1 0.08 1.99 1 0.01 2.01 1 0.01 2 1 0
7
Time constant 0.6 0.62 0.65
Figure 7.1: Graph of flow rate vs time (No.1).
Figure 7.2: Graph of flow rate vs time (No.2).
8
Figure 7.3: Graph of flow rate vs time (No.3).
Figure 7.4: Graph of flow rate vs time (No.4).
9
Figure 7.5: Graph of flow rate vs time (No.5).
Figure 7.6: Graph of flow rate vs time (No.6).
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Part 2: PID controller.
Table 7.2: PID controller
No SP PG
1 2 3 4 5 6 7
2 2 2 2 2 2 2
I
1 1 1 1 1 1 1
D
Steady Theorrtical state offset
0.35 1 0.35 1 0.35 1.9 0.35 2.3 0.35 2.7
1.19 2 1.99 2 2 2 2.01
1 1 1 1 1 1 1
No.
I
D
Steady State
period T
Time constant
1
-
-
1.19
-
-
2
0.35
-
2
2.9
3
1
-
1.99
4
0.35
1
2
5
0.35
1.9
6
0.35
7
0.35
0.81 0 0.01 0 0 0 0.01
0.06 0.07 0.118 0.118 0.116
Theoretical Rise time
Theoretical Peak time
Decay ration
0.462
0.082
2.9
1.45
0.59
6.2
0.987
0
0
0
0
2
7.4
1.178
0
0
0
0
2.3
2
8
1.274
0.071
7.2
4
0.63
2.7
2.01
7.8
1.242
0.001
2
3.9
0.99
2𝜋 𝑇 1 𝑓= 𝑇 𝜔=
𝜋𝜏 √1−𝜑
tp=
Decay ration
damping coefficient
𝜔 = 2𝜋𝑓
r=
Rise Peak Settling time time time (tr) (tp) (ts) 1.01 1.20 2.21 1.25 2.21 7.9 5.3 7.5 7.6 1.51 2.6 10.2 1.75 3.4 12.2 1.85 3.3 12.7 1.93 3.5 13.8
Experimental offset
+ 2
𝜏 1−𝜑2
sin−1 𝜑𝑡
2𝜋𝜑 √1−𝜑2
11
Figure 7.7: Graph of flow rate vs time (No.1).
Figure 7.8: Graph of flow rate vs time (No.2).
12
Figure 7.9: Graph of flow rate vs time (No.3).
Figure 7.10: Graph of flow rate vs time (No.4).
13
Figure 7.11: Graph of flow rate vs time (No.5).
Figure 7.12: Graph of flow rate vs time (No.6).
14
Figure 7.13: Graph of flow rate vs time (No.7).
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8-Discussion: There are two sections in this experiment .the PI and PID section.after obtaining the steady state .when the integer I decrease the flow rate increase at the constant SP and PG .in the chart that makes a wave shapes. for the PID ,at constant SP and PG .we constant the I and D ,when we set the I and increase the D .the settling time increase and the decay ratio decrease. The error may present due to human mistake or apparatus performance.
9-Conclusion: The performance of the control systems is determined by the nature of the process, the characteristics of the controller, the location and magnitude of the disturbance. Sometimes the performance of feedback control system will be unsatisfactory because of large uncontrolled load changes, hence other control schemes can be considered. The best way of using an additional controller to decrease upsets is to use the scheme called cascade control. Output of the primary controller is used to adjust the set point of the secondary controller, which in turn sends a signal to the control valve. The process output is fed back to the controller, and a signal from an intermediate stage of process is fed back to secondary controller. The main advantage of the cascade control is that the performance is better for all types of load changes. For disturbance that enters near the beginning of the system, the secondary controller starts corrective action before the process output shows any deviation.
10-References: Lap manual of process dynamic and control.
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