CHAPTER 1

PRINCIPLES OF AUTOMATIC PROCESS CONTROL

The automatic control is defined as a technique of measuring a process parameter compare it with a desired (or set) value and then producing a counter measure to limit the deviation from the desired value. The

automatic control is also known as closed loop control, because it requires a closed loop of action and reaction performing the task without any human intervention. A closed loop control must have the following

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elements (devices) to accomplish the control of a process variable.

1. Detecting element. 2. Measuring element. 3. Controlling element. 4. Final control element.

The detecting element and the measuring element are usually available in the same housing. Therefore, detecting element and the measuring element together is sometimes called as feedback element. The basic structure of a closed loop control is shown in fig 1.01. The controlling element is a device which operates to limit the deviation of process variable from a desired value. It is popularly known as the controller. The final control element is a device in the control system which directly regulates the flow of energy or mass to the process which in turn affects the process variable to be

controlled. The simplest example of final

control element in process control is control valve. As shown in fig 1.01, the detecting, measuring and transmitting element as combined is known as feedback element. Therefore, a closed loop control means a feedback control. Historical background of Automatic control: The fly ball governor on Watt’s Steam is considered to be the beginning of automatic control. It was invented by J.Watt in early 1780’s. The fly ball governor is a feedback control system based on proportional control principle. Before 1780, there is no known reference to the use of automatic control. The governor techniques were further applied to other engines and steam turbines. The use of automatic control in process started in early 1900’s. Nyquist founded the first general theory of automatic control. By 1940’s the usefulness of automatic control techniques

proved their value.

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Advantages of Automatic control: The one and only advantage of automatic control is that the production is achieved more economically. We can list out many advantages of automatic control, but all the advantages are directly contributing to achieve the production economically. Therefore, the use of automatic control will lead to an increase in productivity. Following are some of the advantages of automatic control directly contributing to increase the productivity.

1. Labor cost is reduced drastically. 2. The use of automatic control

reduces or sometimes eliminates the human error.

3. Product quality is improved. 4. It increases the production level. 5. Equipment size is reduced. 6. Optimizes the energy

consumption. 7. Provides greater safety for

equipment and operating staff. 8. Saving in raw material.

The study and proper application of automatic control is a complex subject. Each application requires detailed knowledge of process, physical and chemical characteristics of process fluids. Apart from this the mechanical aspects of the process equipments like pumps, compressors , heat exchangers , reactors , piping and the control loop is also required . A control application engineer must understand these entire physical, chemical, mechanical and control aspects of process before applying control system for the process control. Theory of Automatic control: Most of the theory related to the automatic control was developed in early 1950’s. Even now the same theory is applied in today’s most sophisticated controllers. The basic control responses that are still used to meet most of the requirements even today are

1. ON-OFF control response (Action) or two position control.

2. Proportional response (Action). 3. Reset (Integral) response (Action). 4. Rate(Derivative) response(Action) 5. Combination of Proportional,

Reset and Rate responses. As these responses are still prevalent today and hence it is necessary to understand these responses as basic inputs to understand the concepts of automatic control theory. ON-OFF (Two Position) Control: This type of control action is used when the process variable to be controlled is not necessarily maintained at a precise value. This is a two step control and the output becomes either of the two positions. One of the two outputs is selected according to polarity of the deviation. In this type of control action, hystersis is added intentionally to increase the life of final control element. In most of the cases the final control element is a relay. If hystersis is not added to the On-Off control, the final control element will operate very frequently and hence its life reduces. The Hystersis is also known as “Differential gap.” The major drawback of On-Off control is that it causes cycling while controlling a process. Fig 1.02 shows On-Off control action graphically. A very simple example of On-Off control is a room air conditioner, which is set at a desired temperature. When the room gets hot, the thermostat turns the compressor on. When enough cold air is circulated to cool the room, the thermostat turns the compressor off. Temperature variations due to cyclic effect usually go unnoticed. Fig 1.03 shows a plot of temperature v/s time and compressor On-Off conditions. When the room temperature is below the desired value, the compressor remains OFF. It remains off till the error becomes zero at which the compressor turns on.

The two position control has wide application in domestic service. The equation for on–off control is m = M1 when e > 0 m = M0 when e < 0 Where m = manipulated variable. e = deviation M1=max value of manipulated variable M0 = min value of manipulated variable

Proportional control: The ON-OFF control has one draw back that it always produces deviations from the desired value in both the directions in a continuous cycle. Such type of cyclic deviations is not at all tolerable by many processes. To overcome the draw back of ON-OFF control, proportional control action is applied. In proportional control action the manipulated variable continuously varies between max. and min. limits.

In proportional control, the output of the

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controller is proportional to the difference between the measured variable and the set point. This difference is called as the error ‘e’. The equation for the proportional control is

m = Kc*e + M - - - - - - - - - - 1.01

Where m = manipulated variable Kc = Proportional gain or

Proportional sensitivity. e = error or deviation. M = constant known as bias

Or manual reset. Equation 1.01 can also be rewritten as

m = (100/PB) e + M - - - - - - - - - 1.02 Where PB = proportional band in % Therefore,

100/PB = Kc - - - - - - - - - 1.03 The proportional band PB is defined as the change in the controlled variable necessary to vary the manipulated variable from 0- 100%. The proportional band or proportional gain is

an adjustable parameter of the controller. It is adjusted in field to tune the controller to give optimum response to the process changes

Fig 1.04 shows the block diagram of proportional control action. The constant M i.e. the manual reset, determines the normal value at zero deviation for manipulated variable. The constant M is called manual reset because it is used to eliminate an offset. An offset always remains with a proportional control. It is clear from the equation 1.01 that the change in manipulated variable is directly proportional to the deviation or we can say that it corresponds exactly to the change in deviation with a degree of amplification. The degree of amplification depends upon the proportional sensitivity or gain. We can hereby conclude that a proportional controller is simply an amplifier with a gain. STEP& RAMP RESPONSES OF PROPORTIONAL ACTION: Fig 1.05 and fig 1.06 show the step and ramp response of a proportional control respectively considering that the manual reset M is zero. When a process is controlled by a proportional action an offset always remains.

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The offset is the value when, in step response, 1. 6

The offset is the value when, in step response, the control deviation has stabilized at a definite value by sufficient laps of time.

Fig 1.07 shows the relationship between the measured span of a controlled variable and a controller output when the proportional band is 100 % or the gain is 1.

Fig 1.08 also shows the relationship between the measured span and the controller output for the proportional band settings of 20, 50, 200& 500% i.e. the gains of 5, 2, 0.5 and 0.2.

The drawback of a proportional control is that the offset always remain with the proportional control.

Let us consider a case of a heat exchanger to see the effect of proportional control on offset. Table 1.01 shows the various conditions of temperature, deviation and valve position for the heat exchanger. Let us consider that the temperature control starts with controller output 0%. At condition I, the set point is 60 degc and the controlled variable is 20 degc, the deviation or the error will be 20-60 = -40 degc and the controller output will be -40*Kc. As a result, the valve opens and the steam flows. Due to steam flow, if temperature increases to 40degc, then the deviation will be -20degc. And the controller output will be -20*Kc. The valve will close a little bit. If water temp increases to 60 degc, then the deviation will be 0 degc

and valve will completely shut. Fig 1.09 shows the graphical representation of change in controlled variable i.e. the water temp with time and the valve opening. The offset can be reduced by

1. Increasing the proportional sensitivity Kc or reducing the proportional band PB.

2. By adding the bias or manual reset. 3. By changing the set point.

A faster stabilization is done by increasing the proportional sensitivity or gain. The stabilization time is reduced by increasing the proportional gain. Thus increasing the proportional gain reduces offset as well the stabilization time. In practical application, there is an upper limit for proportional gain. Extremely high proportional gain would result in oscillation. The oscillation would also be there due to any measuring lag and controlling lag. Integral (reset) control action: Proportional control has one major draw back that offset always remain when load is changed. Therefore, proportional controllers always deviate from set point when subjected to load changes. The offset is objectionable in most of the industrial control systems. To overcome this draw back, integral control action is added with the proportional control. The integral action combined with proportional action eliminates offset.

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Condition Set point (degc)

Controlled variable (degc)

Deviation or error (degc)

Controller output

Valve opening status

I 60 20 -40 -40*Kc Valve opens & steam flows

II 60 40 -20 -20*Kc Valve closes little bit

III 60 60 0 0 Valve closes completely

Table- 1.01 : proportional control of a heat exchanger

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t

In integral control action, the manipulated variable is changed at a rate proportional to the deviation or error. If the error is doubled over a previous value, the final control element moves twice as fast as the previous one. When the deviation is zero, the final control element remains stationary. The integral control action can be mathematically expressed as m = 1 * e - - - - - - - - - - - - 1.04 Ti Or the integrated form is m = 1/Ti ∫ edt + M - - - - - - -- - - - 1.05

where m = manipulated variable. Ti = integral time. e = deviation. M = constant of integration. Thus the effect of integral action is that at steady state, there can be no offset i.e. the steady state error is zero. Fig 1.10 shows the integral control action. The output from a reset control is changed continuously as long as there is an error. The rate of change of the output depends upon the magnitude and the duration of error. Response of integral control action: Response of an integral action to a step input of error e = 0 when t<0 e = a when t≥0 is expressed as m=1/Ti ∫0 a dt) + M -------------- (1.06) m = a*t + M - - - - - - 1.07 Ti When the input becomes zero at t = t1, the output remains stationary. The graphical representation of integral control action is as shown in fig 1.11. The integral time Ti, is defined as the time required in minutes to repeat the proportional correction. Alternatively it can be defined as the time (in PI action), for a step error until the output by only proportional action becomes equal to the output by integral action only.

Proportional Plus Integral Control action: The Integral control action when added with proportional control action to obtain the advantages of both the control actions, then the combined action is known as proportional + integral action. This is also called as PI control action in short. In this control action the output is proportional to the linear combination of the error and the time integral of the error. The PI control action can mathematically be expressed as

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m= Kc(e+1/Ti ∫e dt) + M ---------------(1.08) Where m = manipulated variable Kc = Proportional Sensitivity or proportional gain e = error or deviation Ti = Integral time

The Integral time of PI control action, for a unit step error, is the time that will elapse while the output signal caused by integral control action repeats the output due to proportional control action. The PI control action has two parameters namely Kc and Ti for adjustment. It can be noted from the equation 1.08, that Kc affects both proportional and integral parts of the action. The inverse of the integral time is defined as

the reset rate. It is defined as the number of times per minute that the proportional part of the response is duplicated. It is therefore, called as repeats per minute. Response of PI control action: The response of a PI control action is shown in Fig.1.12.

For a step change of deviation e = 0 t<0 e = a t≥0 where ‘a’ is a constant Substituting these values in eqn 1.08 and then integrating results

t m= Kc (a+a/Ti ∫0 dt) + M --------------(1.09)

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m-M=Kc a (t/Ti +1) --------------------(1.10) Equation 1.10 is a straight line. The term t/Ti is the integral response and the latter is proportional response. The proportional plus integral control action does the same function as proportional plus manual reset. Let us compare PI control action and P plus manual reset control action mathematically. mpi = Kc*e + Kc/Ti ∫ e dt ---------------(1.11) mp = Kc * e + m0 -------------------------(1.12) Here in equation in 1.12, mo is a variable. The function of integral part i.e. K/Ti ∫edt in equation 1.11 is equivalent to function of mo in eqn 1.12. There is a difference in mo of eqn

1.12 of proportional control action and integral part of eqn 1.11 of proportional plus integral control action. The manual reset mo has to be adjusted manually for different load conditions to eliminate the offset whereas integral part of PI control action will adjust the output continuously till the error becomes zero i.e. there remains no offset. Therefore the

advantage of adding the integral mode with the proportional mode is that the integral action of PI control eliminates offset. Derivative control action or rate control action: In this type of control action the output or manipulated variable is proportional to the rate of change of error or deviation. The derivative action is shown in fig 1.13. The derivative control action can be expressed mathematically as m = Td (de/dt) + M - - - - - - - - - - - -(1.13) Where Td = derivative time. The derivative time is the time interval by which the derivative action advances the position of proportional action of the output. By adding derivative action to the controller the lead is added in the controller to compensate for lag around the loop. The temperature loops have large lag and

therefore the advantage of lead in derivative control is appealing for temperature control loops. Because of inherent lead, derivative control restricts the use to limited cases where there is a large inertia or extensive amount of

lag in the process.

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Response of a derivative control action: Fig 1.14 shows graphically the response of a derivative control action for a ramp response. Let error E = at + c.- - - - - - - - - - - - - - (1.14) Then output of a derivative control will be m = Td * d(at+c)/dt - - - - - - - (1.15) or m = Td * a Fig 1.15 shows some more responses of derivative control action for the better understanding of it. The change in output from a derivative control is proportional to the rate of change of error; therefore a derivative control gives a large amount of correction to a rapidly changing error signal. The change in output will be more when the error is small but

changing rapidly. Derivative control is also called as anticipatory control because of the fact that it anticipates the changes in error. Fig 1.16 shows one more response of derivative control only. As the measured variable increases above the set point, the error signal changes. Derivative action is produced only by a changing error signal. A fixed error signal does not change the derivative action output.

Proportional plus derivative control action: The addition of derivative action speed up the response of control loop. Derivative action is very much useful particularly on slow responding systems. It gives both speed and stability of control responses. Its action is opposite to integral action because it leads the proportional action rather than lagging. PD control action is not desirable to the systems where noise error is present. It will amplify the noise errors and lead to instability. Due to this, PD action is not desirable for flow control loops.

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A proportional plus derivative control action can be expressed mathematically as m = Kc*e + Kc*Td*e + M- - - - - - - - - (1.16) Where m = manipulated variable. e = error. Kc = proportional sensitivity. Td = derivative time. M = constant. Eqn 1.16 can also be rewritten as m = Kc(e +Td*de/dt) + M- - - - - - - - - (1.17) Response of PD control action: The response of derivative control action for a step change in deviation cannot be described in a

better way because the derivative of a step change is infinite at the time of change. For this reason, let us consider a linear change of deviation.

Let error e = E t - - - - - - - - (1.18) Where E = constant. The response of PD control action is shown in fig 1.17.

The derivative time in PD control action for a unit ramp error can be defined as the advance in time of the output caused by derivative control action, as compared to the output due to proportional only. It is now clear from the fig 1.17 that the controller response leads the time change of deviation. Therefore we can conclude that derivative control action always add lead to the control response.

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Incomplete derivative action: To minimize the effects of noise, the incomplete derivative action is used. For incomplete derivative action the first order lag is added to a pure derivative unit. The main problems with pure derivative action are

1. Change in output is sudden.

2. Response to noise which is not desirable.

To overcome these problems, first order lag with a time constant td is added to pure derivative. The ratio of Td to td is called derivative amplitude. The block diagram of a first order lag plus derivative is shown in fig 1.18

Response of first order lag plus pure derivative action: Fig 1.19 and Fig 1.20 shows the response of first order lag plus derivative action for step and ramp errors. Practical PD controller: Practical PD controllers are proportional plus derivative with the first order lag added to derivative.

Let td = first order lag time constant. ⁿ = Td/td = Derivative amplitude. Response of practical PD control action: Fig 1.21 and fig 1.22 shows the response of practical PD control action for ramp and step

errors respectively.

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PID CONTROL ACTION: The PID (proportional plus integral plus derivative) control action is an action in which the output is proportional to a linear combination of the error, the time integral of the error and the time rate of change of error. PID control

action can be mathematically expressed as

m = Kc ( 1/Ti * ∫edt + e + Td * de/dt )- - (1.19) Where m = manipulated variable Kc=Proportional gain

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However, the addition of derivative helps to

he block diagram of PID control action is

----------------- (1.20)

Ti =Integral time e = error Td=Derivative time Because of the addition of integral with proportional, overshoot often occurs.

reduce the overshoot. The other advantage of derivative is that it introduces the lead

characteristics which counter the lag characteristics introduced by the integral action. Tshown in Fig-1.23. Let us assume that Error e =E*t ---------Where E= a constant t= time

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nd substituting e in eqn ( 1.19)

= KcE ( 1/Ti * ∫ t dt + Td * d(t)/dt + t ) - - (1.21)

= Kc E ( t / 2Ti + t + Td ) ----------(1.22)

he PID control action for error e = E t i.e

ased upon the discussions of P, I ,D and

ffect of proportional action

A m

2m Tfor ramp error is shown in Fig- 1.24 Bcombinations of P , I & D control actions , we can summarize the effects of control actions in PID control. E By increasing

reases.

es shorter.

ffect of Integral action

the gain or decreasing the proportional band 1. Offset decreases. 2. First overshoot dec3. Control output oscillates. 4. Period of oscillation becom

E By decreasing the

creased

the set point

integral time in PID control 1. offset is decreased 2. first overshoot is de3. control output oscillates 4. time required to return to

becomes less.

Effect of Derivative action: By increasing the derivative time in PID control action

1. offset remains unchanged 2. first overshoot decreases 3. output oscillation is damped 4. oscillation period grows shorter

Modified PID algorithm For a standard PID control, the input to the computation is error. If a set point changes in steps, the deviation will also change in steps. The output of a standard PID controller will also be like a pulse. This pulse like manipulated variable by derivative action disturbs the stability of the process. The step change of manipulated variable by proportional action is also not desirable. To overcome this problem, either the derivative ahead or the proportional ahead algorithm is applied. Fig-1.25 shows the response of a standard PID controller for a step change in set value.

Derivative ahead algorithm

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: In a derivative ahead algorithm, the input to the derivative action is process variable i.e. controlled variable instead of the deviation/error. Because of this manipulated variable avoids a pulse like change by derivative action evenwhen, set point changes in steps. This algorithm is also called PI-D type. The algorithm for a derivative ahead

d as

= Kc [ ( 1 + 1/Ti ∫ dt ) e + Td * dPv / dt ] ---- (1.23)

here ulated variable n

Pv = controlled variable

W m = manipKc = Proportional gai

Ti = Integral time e = error Td = Derivative time The block diagram of derivative ahead controller is shown in Fig – 1.26. The derivative ahead control mode is also known as “Follow up control mode”. This type of control algorithm is selected in cascade control mode. As in cascade control mode, the controller has to control the process not only for disturbances but also for

controller can mathematically be expresse m --------

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st control response r the set point change is required. Hence

is selected

changing set points from other controller or instrument, therefore the fafoderivative ahead control algorithmfor cascade control loops. Proportional ahead algorithm: In proportional ahead algorithm, the input to the proportional and derivative action is controlled variable & not the deviation. Deviation is the input to integral action only. Therefore, the integral action will only

I-PD type and me times constant value control mode.

be xpress d mathematic

ig – 1.27 shows the block diagram of

rol mode, stable ontrol responses are obtained without any brupt change in the manipulated variable for uick change in set point.

ID remain the same for isturbances with the same value of PID

rent

te PID settings for various

respond to the step changes of set points. This algorithm is also called as soThe algorithm for I-PD control action cane e ally as m = Kc [ 1 / Ti ∫ edt + PV ( 1 + Ti * dPv/dt ) ] ------------ ( 1.24 ) Fproportional ahead control algorithm for a step change in set point. It is to be noted that both the control modes described above respond to disturbances as that of standard PID controllers. In proportional ahead contcaq

In derivative ahead control mode, the response to the manipulated variable is quick for a step change of set point. We can conclude now that the responses of PI-D, I-PD and standard Pdparameters. The control response is diffeonly for set point change and depends on the algorithm selected. Approxima

rocessP : Table-1.2 lists the approximate nges, applications of PID settings and

trol responses for various raapplicable conprocesses. Ratio control: Ratio control is used in process to maintain a fixed ratio between two process variables.

he common examples of ratio control in

blending process. The ntrol schemes for ratio control. The basic control schemes for ratio ontrol are

1. Serial type 2. Parallel type 3. External ratio setting

Process

Liquid pressure

Gas pressure

Liquid level

Temp & vapor

omposition

Tprocess are air-fuel ratio in furnaces, feed and catalyst ratio in reactors and mixtures of two materials in

re are several co

c

c

& flow pressure

parameter PB ( % ) 100-

500 0-5 5-50 10- 00 1 100-1000

* 50-200

Integral Essential Unnecessary Seldom Yes Essential

Derivative No unnecessary no Essential If possible Table-1.2: PID settings for various processes

(* for liquid pressure)

Serial type Ratio control scheme:

is called as free flow. The “Fb” is being controlled and hence known as controlled flow. FIC is the flow controller for controlling flow B. The set point for FIC will be the value of a ratio computation o

The serial type ratio control scheme is shown in Fig – 1.28.

n the flow A. The set

station will be 1.1*Fa . As the output of ratio set station is the set point for FIC i.e.

the Fa. This type of ratio control is used in boiler for controlling air to fuel ratio. For ratio control systems, it is necessary that both flow measurements are in the same engineering

As the flow A “Fa” is not controlled, hence it

point for FIC is the output of ratio set station. The ratio set station is a device in which the free flow signal is multiplied by a factor ‘K’ set locally or remotely. Let us assume that the ratio of flow Fa to Fb is to be maintained at Fa/Fb = 1.1 . Fa is a free flow and we have no control on Fa. Then the ratio control will adjust the controlled flow Fb such that it will always be 10 % higher than Fa. The value of K in this example will be 1.1 and the output of ratio set

controller for controlled flow Fb , hence it will always maintain the flow Fb, 1.1 times

units. Parallel type ratio control schemes : Fig – 1.29 shows the control scheme for parallel type ratio control. It is used to eliminate the delay of controlled flow rate which follows the change in free flow. Ka nd Kb are the manual set stations for flow A a

flow B. External ratio setting control scheme : Fig – 1.30 shows the control scheme for external ratio setting control scheme. The output from the analyzer sets the ratio of the

t station so as to keep the % of oxygen in the flue gas constant.

se

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Cascade control: In cascade control two measuring and control systems are used to manipulate a single final control element. The cascade control is used to eliminate the effects of the disturbances entering the secondary process before they influence the primary

process. In cascade control the stability increases. Two controllers are used in cascade control . The higher level controller is called the primary or master controller and the lower level controller is called the secondary controller or slave controller. The higher level controller is called primary because the variable of primary controller is of primary importance. The variable of secondary controller is important, only if it affects the primary variable.

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Fig – 1.31 shows the block diagram of cascade control. For the primary controller the secondary control loop is a part of the process to be controlled. Fig – 1.32 & 1.33 shows a single loop control and a cascade control of a process of heating.

The parameter to be controlled is temp. of the final product. Fig – 1.32 for single loop control shows how the control is accomplished directly with the temperature controller TIC regulating the fuel flow to the furnace. The system of course works with no

problem in controlling the temperature of final product. But what will happen when the disturbance occurs in the flow rate of fuel due to pressure variations of fuel pressure. Due to the measurement lag, the controller will not detect the disturbance immediately. By the time controller TIC detects the disturbance, the control may have lead the process out of normal operation. Cyclic action quite occurs in such case. Fig – 1.33 shows how cascade control operates. In cascade control, the disturbances to the fuel flow rate are controlled before they affect the product temperature. The fuel flow is controlled by a flow controller FIC to maintain the desired fuel flow despite pressure variations in fuel supply. The temperature controller TIC is cascaded with

flow controller FIC. The temperature controller’s output is a set point for flow controller.

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1. 22 1. 22

It must be noted here that cascade control is not applicable for all the unstable process conditions encountered or for all measurement lag problems. However, the cascade control is very much useful to many

process control problems.

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Following are the advantages of cascade control:

1. Disturbances to the secondary control loop are corrected before they affect the primary parameter.

2. Phase lag in the secondary process is reduced by the secondary loop. This improves response and stabilizing time for the primary loop.

3. Non linearity in the secondary process decreases.

Primary direct control for cascade control: Let us assume if the sensor of secondary controller fails, then it will not be possible to control the process. It means that failure of

the sensor of secondary controller will not only affect the secondary loop but it is not possible to control the process as a whole. Primary direct control function is provided in most of the digital controllers.

In case the sensor of secondary controller fails, the output from primary controller i.e. the set point for secondary controller becomes the output of secondary controller to control the process directly as a single loop controller. Cross Limit Control: The cross limit control is very much useful in the combustion control of Boilers. It is used to keep the air to fuel ratio more than the theoretical air to fuel ratio even on change of boiler load. In cross limit control high and low selectors are used to realize the function. The process variable signals given to the selector switch are crossed each other Fig-1.34 shows the scheme of cross limit control for air to fuel ratio control of a boiler.

Process variable of air flow is divided by the air to fuel ratio. Thus both process variables signals, accordingly both set value signals of the controller are the same.

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Boiler load demand signal is given by either a pressure controller or a temperature controller / flow controller. When load increases, the demand increases. The increased demand signal will increase the set points to the selectors. As high select is used for the air flow control, first set point of air flow controller will increase. The air flow then increases. As a result, the set point of the fuel flow controller will increase to increase the fuel. When the demand decreases, at first the set point of the fuel controller will decrease. The set point of air flow will decrease, only when the air flow has decreased. Thus the cross limit control in combustion control always maintains the air rich

condition in furnace irrespective of increase or decrease in boiler load demand. Feed forward control system: Feed forward control is a control in which one or more process parameters are identified that can disturb the control variable. These parameters are used to take corrective action to minimize the deviation of controlled variable. These parameters are not the part of feedback loop. Therefore the application of feed forward initiates a corrective action before a deviation occurs in the controlled variable. The feed forward control prevents the deviation to occur whereas feedback control acts only after the deviation has occurred. It prevents deviation to occur because corrective action is initiated by sensing the change in other process parameter responsible to cause the deviation or disturbance. Split range control: Split range control is a control which has two control valves manipulated by a single controller. Fig - 1.35

1. The size of tubes for pneumatic signal transmission should be large so that the resistance to flow is minimum.

shows a schematic of a steam turbine condenser hot well level control using split range control. The control valve LV-1 is normally used to maintain the hot well level. However, there may be conditions the hot well level may become abnormally low and the valve LV-1 must be closed. In these conditions, valve LV-2 should open to recirculate the condensate to hot well so that the desired hot well level can be maintained.

2. Pneumatic booster relays can be used to decrease the signal response time.

3. Distance of controller from sensing element and final control element should be reduced. It will reduce the distance to be traveled by signal.

Measurement lags

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: It is a delay in sensing the process variable. Measurement lags introduce errors at the time of process changes. If the response of measuring device is slow, inaccurate measurement will be received at controller. The major disadvantage of the measurement lag is that even the large disturbances may go unnoticed if the duration of disturbances is shorter then the measurement lag. Moreover, since the automatic control is continuous, dynamic function the speed of response of the measuring element becomes the essential part of automatic control analysis.

It is normally required to provide a small dead band between valves operation. The percentage of dead band may vary according to the applications. There may be some applications where no dead band is required, and on the other hand there are some applications where an overlap between the valve operations is required. Control system problems: The study of the control system responses in this chapter were made under the following assumptions

1. The measurement lag is zero. 2. The controller lag is also zero. To explain the measurement lags let us consider the case of physical measurement of temperature. If a thermal element is suddenly

temperature of the fluid in the vessel which is at a constant temperature, the response of the

As all the measuring devices in the process have the capacity to store some energy and hence this stored energy opposes the changes to take place. Due to this stored energy the response of a process to a parameter change is likely to be attenuated. This is called as lag. A process control may have different lags like

immersed in vessel to measure the

thermal element will be as shown in Fig-1.36

1. transmission lag 2. process lag 3. measurement lag

Transmission lag: It is defined as the time taken by a measured variable value to be transmitted to its controller to compare with set point and then the time required for manipulated variable to reach the final control element to manipulate it. For electronic signals the transmission lags are negligible. But in pneumatic signals transmission lags are more and can create problem, particularly for fast acting processes. To overcome the problems of transmission lags in pneumatic control system, following actions are taken

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lement gradually increases and approaches

ag

The temperature measured by the thermal ethe vessel temperature. The curve seems to be exponential. The curve shows that if it requires‘t’ sec for the thermometer to indicate 90% of the change, it will take another ‘t’ sec to reach 99% and another ‘t’ sec to reach 99.9% of final value. Because of this lag, theoretically the final temp will never be reached. Process l : Any process can neither store or release energy instantaneously and this

nresult in process lag. These lags are also called as velocity-distance lags or dead time. There is always time required for gas to flow from one point to another to produce a pressure change, or for liquid to flow from one tank to other in a process to produce a level change, or the time required for heat to be transferred from one process to other to produce a temperature change. In all these examples, the time required to produce a change in process variable is a function of velocity of fluid, distance and capacity.