OBJECTIVES: To identify the set point test. To perform the load disturbance test with different manipulated variable. To analyze the type of closed loop process response.

METHODOLOGYOpen loop test1. The process is stabilized either in manual or automatic mode.2. When the controller is in automatic mode and the process has stabilized, it was switched to the manual mode.3. The initial value of manipulated variable, 35 and the initial value of process variable (PVi) were recorded.4. A step change of 4 % was made to the manipulated variable (MV).5. Once the process has increased about 7 to 10% of the process span, MV was set to the 35 or the controller was set to automatic mode, and the process is left to stabilize to the original operating condition.6. The entire event is printed.7. The step is repeated for different value of manipulating variable which is 8% and 12%.Performance test Change in set point 1. The controller was set in automatic mode.2. Change in set point was made to of less than 10% of the process span.3. When the process becomes oscillatory or unstable, the controller was set to manual mode. Then, MV was set to the last stable value.

Change in process loading of Load variable1. The controller was set to manual mode.2. Change of MV value was made to the controller.3. Time taken about 3 seconds was required to the controller.4. Then, the controller was set to automatic mode.5. If the process becomes oscillatory or unstable, the controller was set to manual mode. Next, MV value was set to last stable value.

EXPERIMENTAL RESULT AND DATA ANALYSIS1)

= 4%a= b = PV = 8mmTd = 1mmRR =( ()RR= () = 0.4696/sTd = 1mm x = 1.304 sPV = 8mm = 8mm x = 4.706%Tc =(Pvf Pvi ) () ( ) = 4.706( ) ( = 2.505 sP = 110RRTd = 110(0.4696)(1.304) = 67.359%

I = 3.3Td = 3.3(1.304) = 4.3032 s

Kc = = = 1.485

2)

= 8%a= b = PV = 16mmTd = 0.5mmRR =( ()

RR= () = 0.4011/sTd = 0.5mm x = 0.652 sPV = 16mm = 16mm x = 9.412%

Tc =(Pvf Pvi ) () ( ) = 9.412( ) ( = 2.933 s

P = 110RRTd = 110(0.4011)(0.652) = 28.77%

I = 3.3Td = 3.3(0.652) = 2.152 s

Kc = = = 3.476

3)

= 12%a= b = PV = 25mmTd = 0.1mmRR =( ()

RR= () = 0.3299/sTd = 0.1mm x = 0.1304 sPV = 25mm = 25mm x = 14.706%

Tc =(Pvf Pvi ) () ( ) = 14.706( ) ( = 3.715 s

P = 110RRTd = 110(0.3299)(0.1304) = 4.732%

I = 3.3Td = 3.3(0.1304) = 4.732 s

Kc = = = 21.133

RESULT

(%)RR (s-1)Td (s)Tc (s)P (%)I (s)Kc

40.46961.3042.50567.3594.30321.485

80.40110.6522.93328.772.1523.476

120.32990.13043.7154.7320.430321.133

Types of Closed Loop Process Response

(%)PB (%)I (s)Set point testLoad disturbance test

467.44.3OverdampedOscillatory

828.82.2UnstableUnstable

124.70.4UnstableUnstable

Note : Proportional (P) and Integral (I) is calculated by using Takahashi Tuning rule.

DISCUSSION

The experiment has been conducted by using Flow Indicating Controller 21 (FIC 21). The objective of this experiment is to analyze the closed loop process response based on 3 different manipulated variables (MV). The values of manipulating variable used are 4%, 8% and 12%. Different values of manipulating variables will result in different value of proportional (P) and integral (I) . Since the experiment is a flow process control which resulting the fast process response, the mode of control used is P+I. Takahashi Rules have been used in order to obtain the value of controller gain (Kc) and integral time ( I ) .Based on the experiment, there are several steps that need to be considered in order to obtain the results (graphs) for each manipulated variable. The initial MV is set up at 35% . A change in manipulating variable (MV) of 4% is made. Thus the final value of MV is 39%. 4 % of change in MV will produce changes in the process for the optimum PID calculation. The initial set point is 2.0 m3/h . For this (MV), the response rate (RR) obtain is 0.4696/s, dead time ( Td ) is 1.304 s and time constant ( Tc ) is 2.505 s . The proportional (P) and integral (I) are 67.36 % and 4.3032 s respectively. Then, the controller gain (Kc) obtained is 1.485 . For second graph, the optimum Proportional (P) and Integral (I) calculated from the Takahashi rule has been tested for graphic performance analysis. When testing the performance of Proportional(P) and Integral(I), a change in set point has been made to of less than 10% of the process span which is 2.1 m3/h . From the first graph (Figure 2) of process response obtained, it can be seen that the graph of process response to set point (SP) test is overdamped. The process is reaching the set point requirement. For the load disturbance test, 5% value of MV has been made to the controller . The graph for the load disturbance test is oscillation at the set point. Second, manipulating a variable change (MV) is 8%. The response rate (RR) is 0.4011/s, dead time ( Td ) is 0.652 s and time constant ( Tc ) is 2.933 s . The proportional (P) and integral (I) are 28.77 % and 2.152 s respectively. Therefore, the controller gain (Kc) obtained is 3.476 . For this MV , the graph ( Figure 3a ) for the set point (SP) test shows that the process response is unstable condition . This is, the same goes to load disturbance test. In order to stabilize the unstable process response, the value of Kc has been divided by 4 (Kc /4) while the value of I is multiplied by 4 (Ix4) . Thus, the new Kc and I are 0.869 and 8.608 s respectively. The stable process response can be seen in Figure 3b.The last manipulating variable change (MV) is 12%. The response rate (RR) is 0.3299/s, dead time ( Td ) is 0.1304 s and time constant ( Tc ) is 3.715 s . The proportional (P), integral (I) and controller gain (Kc) is 4.732 %, 0.4303 s and 21.33 respectively. From the graph in Figure 4a, it can be seen that the process response is quite unstable for both set points (SP) test and load disturbance test. In order to get the stable response such in Figure 4b, the value of Kc has been divided by 16 (Kc /16 ) while the value of I is multiplied by 16 (I16) . So that, the new Kc and I are 1.321 and 6.885 s respectively.Based on the graphs obtained, the different value of MV will result in a different type of process response. The lowest change in manipulating variable (MV), the more stable process response. From the result of the experiment, MV 4% has the best process response since it is the only one that stable. Basically, the large value of proportional (P) typically means faster response since the large error is occurred. In Figure 4a, an excessively large proportional gain (Kc) will lead to process instability and oscillation. On the other hand, an excessively small integral (I) term such as in Figure 4a causes the present value to overshoot the setpoint value which resulting in instability process response.Figure 2 (closed loop graph 1) shows that a small Kc results in a small output response to a large input error. It is a less responsive controlled which means the process is slow. Since the Kc value is too low, the control action is small when responding to a system disturbance. Generally, the purpose of using Integral control is to eliminate the offset of the process response since the controller output depends on the integral of the error signal over time. When an error is equal to zero, no offset has been produced by the process.

CONCLUSION

There are several conclusion that have been obtained from this experiment. First of all is the value of MV played the major role in this experiment which controlled the Kc and I, the smallest the value of MV. The more stable the graphical process response will be. On the other hand, when the gain is greater, the output from the input will be also greater. The increasing of gain, Kc the larger in error may obtained cause by the unstable loop. Other than that, in order to stabilized the oscillatory process response, the value of Gain,Kc and Reset, I must be divided and multiple respectively by 2, 4 or 16.

APPENDIX13