ABSTRACTIn almost all processes exist in the industry utilizes process control loop systems to ensure better control and safety of the process. A typical control loop in a process is made up of four basic control blocks namely the sensor, process, controller and final control element. An open control loop is where controller is set to manual and closed loop is when controller is in auto mode. The Automatic control uses algorithm consisting of proportional, integral and derivative. The objective of the lab work is to perform open loop test, closed loop test, Load disturbance test and set point test using Foxboro and Emerson controllers systems. The processes which these test are conducted on are pressure control, level control and flow control. The open loop curve is obtained and the values of P,I and D are calculated using Ziegler Nichols and cohen coons tuning rules. The P, I and D values are then used for closed loop test, load disturbance and set point test. It is found that there still oscillations occur and the value of P needs to be change to prevent oscillations.

CHAPTER 1

1.1 INTRODUCTIONProcess control relates to statistics and engineering used for maintaining the output of a certain process within the desired range. The term control refers to the regulation of the process. Process control includes designing process system, identifying instrumentations and also determining the right parameters for controllers. Types of control system include feedback, cascade, feed forward and also ratio. In specifying instrumentation, the process is identified whether involves flow, level, temperature or pressure. Specifying instrumentation also involves the identification of control valves and also control signals. Selecting right parameters however involves in either to adjust the proportional (P), integral (I) or the derivative (D) of the control system. Implementation of process control has the potential to reduce defective products and also provide precise measurement and control. However, the implementation of process control requires high cost of instrumentation and not to forget highly trained workers in automation.Some basic terminologies related to process control are controlled variable or process variable PV, manipulated variable (MV), set point (SP) and also disturbance or load variable. Process variable refers to the variable that must be maintained at desired value whereas manipulated variable refers to the variable used in order to maintain the process variable. Set point refers to the desired value of process variable. On the other hand, load variable is defined as any variable that causes the process variable to diverge from its set point. A process control loop consists of four blocks. The four blocks are controller, final control element, process and sensor. The controller acts as a brain of the control loop. It performs decision in the control system. Final control element such as control valve implements the decision performed by the controller. Sensor acts by transmitting signals obtained from process to the controller.A feedback control involves a process in which the outcome of an action is fed back to the controller for corrective measures. On the other hand, cascade control involves inner loop and outer loop. This type of control functions by the inner loop controller receives its set point from outer loop controller. Cascade control is mainly used to eliminate effect of disturbance. A feed forward control is described as a method of control that is based on process model. Its objective is to deal with disturbance before they affect the controlled variable.

As mentioned earlier, a process control loop consists of four control blocks which are controller, final control element, sensor and process. A system is considered as closed loop system when all of the four control blocks are connected. This means that, the controller will compare the controlled variable outcome with the desired set point and will makes necessary changes for corrective action to the final control element such as control valve. The advantage is that production can be maximized through the application of automatic closed loop control. Other than that, the automatic closed loop control can also produce the products at desired standards. Closed loop system is as shown by the Figure 1.1 below:

PVMVSPPFinal Control ElementController Process

PV

Sensor

Figure 1.1: Closed loop controlHowever, if any one of the four control blocks is disconnected, the process control loop is the called open loop system. In an open loop system, the correction of final control element is done manually by an operator which indicates that the controller has no control over the final control element. Figure 1.2 below shows an open loop system:

PVMVSPPProcess Final Control ElementController

Operator PV

Sensor

Figure 1.2 : Open loop controlPID controller is one of the most common forms of closed loop control. The term PID stands for proportional, integral and derivative. The controller takes a measured value from a certain process and compares it with the set point value. The difference between the measured value and the set point or also known as error signal is then used to adjust the input to the process so that the measured value will be at the desired set point. Outputs of process can be adjusted based on history and rate of change of error signal by using PID. PID controllers can be easily tuned to the desired application. The common PID control equation also referred to independent gain algorithm is shown below:CO = KP.E + KI + KD Where, CO = Controller Output, KP = Proportional Constant, KI = Integral Constant, KD = Differential Constant, t = Time

and the error, E is defined as E = (Process Variable Set Point) (direct action) or,E = (Set Point Process Variable) (reverse action)

An increase in the process measurement of direct acting control loop will cause an increase in the controller output. Besides the equation shown above, there is another form of PID equation called the ideal algorithm. The equation for ideal algorithm is as shown below:CO = KC (E + + TD )

Where, KC = Controller Gain TI = Reset Time TD = Rate Time

Even though the independent gain algorithm equation uses the second time domain whereas the ideal algorithm equation uses minute time domain, both of the equation are actually the same with the following conversion: KP = KC KI = KC / (TI . 60) KD = KC. TD. 60

However, there is another type of PID equation which is shown by the following equation:CO = KC (E + )(1 + TD )

Proportional and integral modes commonly are used as single control modes. However, a derivative mode is rarely used as single control mode in a control system. Some of the popular combinations in practical systems are PI and PD control.

When parameters of an existing controller have to be tuned, there will be a problem in the identification of PID controller. Controller structure has to be determined since manufacturers do not provide data on controller structure whether serial or parallel. Manual tuning of controller parameters had to be done if they are changed with time. Other than that, manual tuning of controller parameters also had to be done when change in process parameters occurred. Manual parameter tuning can be done using trial and error and if rules shown in the table below:

ParameterSpeed of ResponseStabilityAccuracy

Increasing KIncreasesDeteriorate Improves

Increasing KiDecreasesDeteriorate Improves

Increasing KdincreasesImproves No effect

Table 1.1 : Parameter of KUnfortunately, if it is not possible to tune the controller parameters using trial and error method, then it is important to know the controller structure. The controller structure can be identified using a certain type of reference signal on the controller input and measuring response on the controller output.

CHAPTER 22.1 THEORY2.1.1 Graphical Tangent MethodThis method is used in the calculation to find RR and graphically find Td. RR and Td is found on a process curve graph.

PViPVfPVTangent LineTdtTimeTimeMViMVfMV

Figure 2.1 : Graphical Tangent MethodDead time (Td) is the time between the beginning of the open loop test to the foot of the triangle. The dead time is measured directly on the graph (using ruler).For Tangent Method, t is equal to Tc which is the time constant of the process. It is from the front foot of the triangle (after the end of Td) towards the end of the triangle as shown on Figure 2.1. Like Td, Tc is measured the same way on the graph.

The response rate, RR is calculated by:RR = (PV/t)/ MVWhere,PV = PVf PViMV = MVf MVi

2.1.2 Reformulated Tangent Method

PViPVfPVTangent LineTdtTimeTimeMViMVfMVab

Figure 2.2 : Reformulated Tangent Method

Reformulated Tangent Method is an alternative to tangent method and is quite similar. Instead of calculating the RR using distance by a ruler, reformulated tangent method allows the calculation in forms of trigonometric functions.Based on figure 2.2, There are angles and and on the both of the axis there are b and a. b and a are scaling factors to be used in the calculation of RR.Dead time, Td is calculated by,Td(time) = Td(length by ruler) x bWhere,b = (increment of time on the axis scale)/(length of each interval)The response rate, RR is,RR= ((tan )/MV)(a/b)Time constant, Tc is,Tc(time) = Tc(length) x b

2.1.3 Discrete Tangent Method

PViPVfTime(Td , PVi)(Td , PVi)Tangent LinehPV-1PVoPV1t-1t-ot1

Figure 2.3 : Discrete Tangent Method

Some data are in the forms of numerical and tables. In discrete tangent method, calculation of response rate RR, dead time Td and time constant Tc to be calculated for numerical data. This numerical method requires no measuring on graphs but requires numerical calculation from the data tables obtained from the process. Figure 2.3 shows what the graph looks like if plotted from the data tables.To calculate response rate,RR = (PV1 PV-1)/2hMVThe time constant, Tc,Tc = 2h [(PVf PVi)/(PV1-PV-1)]The dead time Td,Td = t1 2h [(PV1 PVi)/(PV1-PV-1)]2.1.4 Ziegler-Nichols Tuning rulesIn Ziegler-Nichols tuning rules, only requires values of RR and Td. These values are the ones calculated from tangent, reformulated tangent or discrete tangent method. Performance tests are in terms of set point and load disturbance.Below is a table for calculating respective values of P,I and D.ModePID

P3.33RRTd

PI111.1RRTd3.33Td

PID83.3RRTd2Td0.5Td

Table 2.1 : PID tunes

2.1.5 Cohen-Coon Tuning RulesAnother Tuning rule is Cohen-Coon Tuning rules. For this tuning rules require values of RR, Td and Tc. Performance test is in terms of load disturbance variable.ModePID

P[100/(1+/3)]RRTd

PI[100/(1+/11)]RRTd3.33[(1+/11)/(1+11/5)]Td

PID[100/1.35(1+/5)]RRTd2.5[(1+/5)/(1+3/5)]Td0.37Td/(1+/5)

Table 2.2 : PID tunes

2.2 PROCEDURE 2.2.1 DCS Delta-V Emerson (FLOW)2.2.1.1 Liquid Flow PlantOpen Loop Test for FIC211. The Liquid Flow Plant, FIC21 was selected.2. After the overall diagram of the plant has opened, the controller of FIC21 was double clicked to open the faceplate. 3. The Process History View was clicked to see the trend of the process.4. The process need to be stabilized in manual. 5. The initial value of MV was recorded and the step change of 10% was taken.6. After the response has reached the steady state, the response graph was printed and calculation for obtaining the RR, td and tc. 7. The calculated value of PI controller was obtained by using Ziegler-Nichols and Cohen-Coon method. Closed Loop Test for FIC211. The controller was set to auto mode. 2. The detail icon was clicked at the faceplate in order to set the controller setting.3. The calculated value of Gain, Kc and Reset, I was entered in the detail. 4. After the response has reached the steady state, the value of the optimum PI controller was recorded. 5. Load disturbance test was done by turn the process into Manual mode and make a step change of MV by 10% for three second and change into Auto mode again. 6. After the process has stabilized, the process response after changed the MV was observed.7. The set point test was done by adding the previous set point with 10% from total value which is 0.6m3/h. 8. After the process response has reached the steady state, the response was observed.9. Both graph for load disturbance test and set point test was printed.

2.1.1.2 Gas Pressure Control PlantOpen Loop Test for PIC921. The Liquid Flow Plant, PIC92 was selected.2. After the overall diagram of the plant has opened, the controller of PIC92 was double clicked to open the faceplate. 3. The Process History View was clicked to see the trend of the process.4. The process need to be stabilized in manual. 5. The initial value of MV was recorded and the step change of 10% was taken.6. After the response has reached the steady state, the response graph was printed and calculation for obtaining the RR, td and tc. 7. The calculated value of PI controller was obtained by using Ziegler-Nichols and Cohen-Coon method. Closed Loop Test for FIC211. The controller was set to auto mode. 2. The detail icon was clicked at the faceplate in order to set the controller setting.3. The calculated value of Gain, Kc and Reset, I was entered in the detail. 4. After the response has reached the steady state, the value of the optimum PI controller was recorded. 5. Load disturbance test was done by turn the process into Manual mode and make a step change of MV by 10% for three second and change into Auto mode again. 6. After the process has stabilized, the process response after changed the MV was observed.7. The set point test was done by adding the previous set point with 10% from total value which is 2.5 psig 8. After the process response has reached the steady state, the response was observed.9. Both graph for load disturbance test and set point test was printed. 2.1.2 DCS FOXBOROOpen Loop Test for LIC311. The Level Control Plant, (WLF922) was selected.2. LIC31 was selected for the control loops.3. For viewing the trending, the step are by clicking the File>Additional FoxView>Change Env(The environment was change to operator). 4. Double clicked at the controller at the new windows of WLF922, then trend button was clicked. 5. The process response was stabilized by setting the process in Auto mode. 6. The initial value of MV was recorded.7. The process was changed to manual mode and step change of 10% of MV from the initial was done. 8. After the slope can be calculated, the process was changed to Auto mode again.9. The data for the process was printed by selecting the AIM Historian Data Display and desired data was tagged which are SP, PV and MV.10. Numerical analysis was done to obtain the data of RR, td and tc. 11. The determination of PI controller setting was calculated using the Ziegler-Nichols method. Closed Loop Test for LIC311. After the calculated value of PI was done, the value then were inserted into the controller setting of PB and I.2. After the response has reached the steady state, the optimum controller setting were recorded. 3. The load disturbance test was done by changing the process response into Manual mode and change 10% of the current value was done for three seconds and set to Auto again.4. The response was observed until it stabilized. 5. The set point test was done by adding the previous value set point with 10% of total value which is 80m3/h.6. The response was observed until it stabilized.7. The process response than was printed by following the step START>Program>HyperSnap-DX>HyperSnap-DX>Capture>Active Window.8. The trending active window was selected and then the image was inverted to black and white. The process response than was printed.

CHAPTER 33.1 RESULTS AND DISCUSSION

MVi: 60 %PVi : 64.5 %MVf : 65 %PVf: 74 %MV: 5 %PV: 9.5 %a: 5 %/14 mmb: 60 s/50 mm3.1.1 Flow controller

Td Time constant, TcTc = Response rate, RRRR = = 3.1.1.1 Optimum controller setting ( Ziegler-Nichols method)P = 111.1 RR Td = 111.1 0.792 0.6 = 52.795 %

I = 3.33 Td = 3.33 0.6 = 1.998 s

3.1.1.2 Optimum controller setting ( Cohen-Coon method) P = = = 46.46 %

I = = = 2.03 s

3.1.1.3 Open loop testFor flow control, the system is self regulating. This means that the system must be carried in MAN mode. After the process has been stabilized, change to MAN mode and make a step change to the MV value. In this case, the MV is changed from 60 % to 65 %. P+I mode is chosen because the process is fast and no further adjustments need to be made. The process slope can be used to calculate the time constant, dead time and response rate. These values are important for calculation of P and I in closed loop test.

Figure 3.1: Open Loop3.1.1.4 Closed loop testThe closed loop test is done by using the value of P and I calculated from two methods, Ziegler-Nichols and Cohen Coon method.

Figure 3.2 : Ziegler-Nichols method

Figure 3.3 : Ziegler-Nichols method

Ziegler-Nichols For Delta-V Emerson model, Kc value is used instead of P value. Kc value can be calculated by Kc=100/P. After the Kc and I value are inserted, the process looks oscillatory and the value of Kc need to be changed. The value of Kc is reduced 4 times by dividing the value by 4 each time. Then, the process starts to move towards set point. The load disturbance test is done in MAN mode and quickly back into AUTO mode after changing the MV value. The response is fast and moving towards set point because the value of Kc and I are accurate. The same goes for set point test and shown no oscillations or errors.

Figure 3.4 : Cohen coon method

Figure 3.5 : Cohen coon method Cohen-Coon After the value of Kc and I are inserted, there is one oscillation and the process moving right towards the set point after that. This shown that there is no need to change the value of Kc and I because the process has stabilized quite fast. The load disturbance test shown that the process response oscillates once before it move towards the set point. The set point test shown that the process oscillates a few times but it is normal because the set point is changed and the original values of Kc and I for previous set point is not the same as the new one. Every set point has its own Kc and I values.

3.1.2 Pressure Controller

MVi: 65 %PVi : 76 %MVf : 70 %PVf: 82 %MV: 5 %PV: 9.5 %a: 10%/17 mmb: 15 s/11 mm

td = 2mm x 15s/11mmtc = 9mm x 15s/11mm = 2.723 s = 12.273 s

By using tangent method, tc = tRR = = = 0.0978 s-1

3.1.2.1 Optimum Controller Setting Based on Ziegler-NicholsP = 111.1RRtd = (111.1)(0.0978 s-1)(2.723 s) = 29.587

I = 3.33td = (3.33)(2.723 s) = 9.068 s

3.1.2.2 Optimum Controller Setting Based on Cohen-Coon = td/tc = 2.723 / 12.273 = 0.222P = = 26.137 I = 3.33()(td) = 6.224 s 3.1.2.3 Open Loop TestFor this test, the controller has no effect towards the final control element where the adjustment must be done by the operator in order to see the differences. For gas pressure, the process behaviour is self-regulating and fast response which means that it can stabilize by itself and have the final steady state fast. The P+I mode was choose due to the fast response of the process. Thus, the calculation for P and I must be done for fine tuning process in closed loop test and the manipulated variable, MV was change to + 10% because to get the optimum PID calculation.The analysing for the response rate, RR, dead time, td, and constant time, tc, were done because these three are the important parameter for optimum controller setting.

Figure 3.6 : Open Loop

3.1.2.4 Closed Loop TestIn the closed loop test, the parameter that been change is the gain, Kc and the derivative, I. Kc was obtain from 100/P.

Figure 3.7 : Ziegler-Nichols method

Figure 3.8 : Ziegler-Nichols method

Ziegler-Nichols No fine tuning need to be done because the calculated Kc and I make the process move towards set point. The load disturbance test required by changing the MV to 10% for three seconds which is from 42% to 52%. The response was underdamped before it moves toward the set point. The time taken for it to stabilize at the set point was fast and shows that the calculated Kc and I were right because short time was taken to stabilize the response and move towards set point. The set point test was done two times because the change in the first set point test was small. The changes of the set point should be done by 10% of total of set point which is 25 psig. The changes for the first set point test did not give difference between before the set point test done. Thus, second set point test was done from 11 to 13.5 psig. The response shows that the PV was oscillate around the set point line. This shows presence value of Kc and I was not suitable for the new set point thus new value of Kc and I need to be calculated.

Figure 3.9 : Cohen Coon method

Figure 3.10 : Cohen Coon method Cohen-Coon Fine tuning was done for the process the response was oscillate rapidly where the value of Kc were divided 4 three time before it reach the set point. The load disturbance test where 10% difference of MV which is from 55% to 65% shown that the response underdamped before it move towards the set point. The length of time taken for the response to settle at the set point was about 1 minute and 20 seconds. This is because, the response is self-regulated and stabilise by itself. The set point test was done by change 10% from the total set point which is 6 m3/h. The response show same condition when using the Ziegler-Nichols calculation to calculate the P and I. The process oscillate when the set point was changed and it done not stabilize at the set point. Though the response is self-regulated, the entered value of Kc and I did not move the response towards set point. This shows that new value of Kc and I need to be obtained for the process to become stable at the set point. 3.1.3 Level controllerTime (s)MV (%)PV (mm)PV (%)Response rate (s-1)

024.09426.8853.360

134.00425.1753.15-0.042

234.00423.5352.94-0.031

334.00422.7352.84-0.003

434.00423.2852.910.012

534.00423.6952.960.011

634.00424.1653.020.009

734.00424.3853.050.012

834.00425.1153.140.012

934.00425.3653.170.011

1034.00425.9853.250.008

1134.00425.9853.250.011

1234.00426.8853.360.02

1334.00427.5653.450.013

1434.00427.9253.490.006

1534.00428.0553.510.009

1634.00428.6453.580.014

1734.00429.2353.650.013

1834.00429.6653.710.006

1934.00429.6653.710.009

2034.00430.4153.800.015

2134.00430.8453.860.013

2234.00431.4553.930.011

2334.00431.7753.970.013

2434.00432.5054.060.018

2534.00433.2254.150.014

2634.00433.5654.200.006

2734.00433.6954.21-5.42

MVi: 24.09 %SP: 400 mmMVf: 34.00 %PVT: 800 mmMV: 9.91 %PVi: 53.36 %h: 1 sPVf: 54.21 %

To change PV (mm) to PV (%)

= Response rate, RRRR = RR1 = = -0.042From the table, notice that RR increases until time = 8 s, then it keeps decreasing. Response rate for this process is taken at maximum RRRRmax = RR4 = 0.012 s-1

Dead time, TdTd = = = 11.67 s

Time constant, TcTc = = = 14.17 s3.1.3.1 Optimum controller setting ( Ziegler-Nichols method)P = 111.1 RR Td = 111.1 0.012 11.67 = 15.56 %

I = 3.33 Td = 3.33 11.67 = 38.86 s

3.1.3.2 Open loop testFor level control, the system is a non self regulating. So to stabilize the process, it must be changed to MAN mode. Once the process stabilized, change the MV and in our case the MV is changed from 24 % to 34 %. Short time after that, change the process back to AUTO mode. The set of data from the time of change of the MV is collected for further calculations. From the numerical data, dead time (Td), response rate (RR) and time constant (Tc) can be calculated. The maximum response rate is obtained at time, T: 4 seconds. This means that after 4 seconds the process slope move downwards for the first time after moving upwards.

Figure 3.11 : Open Loop3.1.3.3 Closed loop testThe closed loop test is done by using Ziegler-Nichols method to find the value of proportional, P and integral, I. The Cohen-Coon method is not used for closed loop test in Foxboro model. For Foxboro model, the P value can be directly inserted because Kc value is not used. After the value of P and I have been inserted, the process shown no oscillations and directly stabilized. This means the value of P and I are accurate for the process and no further adjustments needed. For set point and load disturbance test, the process is not oscillatory and move towards set point.

Figure 3.11

CHAPTER 4

4.1 CONCLUSION Based on the tests for open loop, self regulating system must be run in manual mode and left to become stable in order to calculate time constant, dead time and response rate. Self regulating systems are pressure and flow. For non-self regulating system which is the level controller, the system is left in manual mode until slope can be calculated from the graph. Basically, Open loop test helps to determine values P and I for the closed loop test.After the closed loop tests, it was found that there are still oscillations occur even after the P and I values are calculated using different tuning rules. The oscillations can be reduced by manipulating the values of P and I. This is called fine tuning. The value of P is decreased by dividing by 4 until the oscillations reduced. The Value of I is increased by multiplying by 4 to further decrease the oscillations. Level and pressure control in this test have no oscillations from the P and I calculated while flow does have oscillations and require fine tuning.For Load Disturbance test, Level and flow controller process have no oscillations occur which shows correct values of P and I. Pressure controller however, appears to be underdamped before process reaches set point therefore, the P and I values may not be accurate. From Set point tests, flow and level have no oscillations but pressure have oscillation and its Kc must be changed.

4.2 RECOMMENDATIONS1. Calculation of RR should be four or more decimal places. This may give more accurate data and leads to better values of P, I and D.2. The eyes position when measuring the distance on the graph for Td and Tc must be perpendicular to the ruler to avoid parallax error.3. While fine tuning, if process oscillates, adjust the P (by dividing by 4). If oscillation persists, keep reducing the P.4. It is recommended to adjust P and I values one by one not simultaneously. Adjusting P and I simultaneously can lead to worst oscillation of the process or even leads to offset.5. There are other methods for RR and Td calculation for the open loop such as Reformulated Tangent Method. These methods could also be used and compared with the current method used in this experiment so that the data could be more feasible

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APPENDICES20