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Industrial process control
Definitions
Process
It Is defined as:

• Physical or chemical change of matter.
• Energy conversion

e.g., change in pressure, temperature, speed, electrical
potential, etc.

A       process        in     a       collection     of
vessels, pipes, fittings, gauges etc., is built for the
purpose of producing a product or group of products.
Process Control
The regulation or manipulation of variables influencing
the conduct of a process in such a way as to obtain a
product of desired quality and quantity in an efficient
manner.
Input to Process: Mass or energy applied to the process.

Output of Process: The product delivered by the
process. This is a dynamic variable.

Supply: Source of mass or energy input to process.

Control Valve: Consists of the final actuator and final
controlling elements. This is the forward controlling
element which directly changes the value of the
manipulated variable.

Load: Anything that affects the value of the controlled
variable under a constant supply input.
Open Loop: Control without feedback. Open loop can not
cope with load upsets. Example of open loop: automatic
dishwasher, automatic water sprinkling system, a control
loop with the controller in manual.

Primary Element: The measuring element that
quantitatively converts the measured variable energy
into a form suitable for measurement.

Transmitter: A transducer which responds to a measured
variable by means of a sensing element, and converts it
to a standardized transmission signal which is a function
only of the measured variable.
Controlled Variable: A variable the value of which is
sensed to originate a feedback signal. (Also known as the
process variable.)

Controller: A device which operates automatically to
regulate a controlled variable.

Controller    Algorithm      (PID):     A    mathematical
representation of the control action to be performed.

Set Point: An input variable which sets the desired value
of the controlled variable.
Error: In process instrumentation, the algebraic
difference between the real value and ideal value of the
measured signal. It is the quantity which when
algebraically subtracted from the indicated signal gives
the ideal value.

Manipulated Variable: A quantity or condition which is
varied as a function of the algebraic error signal so as to
cause a change to the value of the directly controlled
variable.
Feedback Control: Control action in which a measured
variable is compared to its desired value to produce an
actuating error signal which is acted upon in such a way
as to reduce the magnitude of the error.

Cascade Control: Control in which the output of one
controller is introduced as the set point for another
controller.

Feedforward Control: Control action in which
information concerning one or more conditions that can
disturb the controlled variable is converted, outside of
any feedback loop, into corrective action to minimize
deviations of the controlled variable.
Industrial process control
Industrial process control
Industrial process control
Open Loop Control
The operator walked up and down a plant, looking at gauges
and opening and closing valves is effective only at the time
when the operator moves the valve.

At that instant the loop is closed.

Open loop control works only when the load(s) on the
process are constant.

Any load change or supply upset can affect the product
quality.
Advantages of Closed Loop Control
Increased productivity: Automatic closed loop control allows the
amount of products made in a particular process to be maximized.

On Spec Products: Industrial products are produced to meet
certain purity levels.

Energy and Material Conservation: A closed loop control
application minimizes the amount of material and energy used in
production.

Safety: Closed loop control is the first line of defense before
Emergency Shutdown Devices (ESD) override regulatory control
devices.
Types of Control
• Continuous Control is used on continuous processes. A
continuous process is one in which process material is
continually flowing through the process equipment.

• Sequential is often referred to as on/off control. It is a
series of discrete control actions performed in a specific
order or sequence.

• Batch control is a combination of sequential and continuous
control. A batch process is a process where the operation is
time-dependent and repeatable.
Positive Feedback

•It can be defined as the control action in which the error is
reinforced until a limit is eventually reached.

•This obviously is not a desirable outcome of control action
and should be avoided.

•Imagine a tank in which level is being controlled. When the
level exceeds the set point, the control action will increase
the level further until the tank overflows.
Negative Feedback

•It can be defined as the control action in which the error is
minimized, made as small as possible, depending on the
algorithm of the controller.

•This obviously is a desirable outcome of the control action
and should be achieved in all feedback loops.
Direct Acting Element is one in which the value of the output
signal increases as the value of the input signal increases.
Reverse Acting Element is one in which the value of the
output signal decreases as the value of the input increases.
Control Valves

A control valve consists of a valve connected to
an actuator mechanism. The actuator, in
response to a signal from the controlling
system, can change the position of a flow-
controlling element in the control valve.

The action of the final actuator is the first choice
and is based on “Fail-Safe Control Valve Action”.
(open, closed, and in place).
Industrial process control
Industrial process control
Transmitters
It can be set up (calibrated) as either direct acting
or reverse acting.
Processes
It can be either direct or reverse acting.
Most processes are direct acting.

Energy Flow Process
1.Heat Exchanger
2.Refrigeration

Mass Flow Process
1. Level Tank
2. Pipe Flow
Industrial process control
Industrial process control
Industrial process control
Industrial process control
Rule for Achieving Negative Feedback
To achieve negative feedback in a control loop you must
have an odd number of reverse acting elements in the
loop.
The odd number of reverse-acting elements for
negative feedback can be determined through
an open loop test, conducted in the following
manner.

Place the controller in manual (open loop), and
step up the output of the controller (5-10%) and
observe (record) the output of the transmitter.
Industrial process control
Control Loop Elements And
Their Contribution To Loop Performance
Transmitters
Accuracy (Error) = Precision Error + Bias Error
Range: The region between the limits within which a quantity is measured
is the range of that measurement.

Span: The measurement span is the algebraic difference between the
upper and lower range values.

Minimum Span : The minimum span of measurement that the primary
element can be used to measure within its accuracy rating.

Maximum Span: The maximum span of measurement that the primary
element can be used to measure within its accuracy rating.

Rangeability (Turndown): In flow applications, rangeability is the ratio of
the maximum flow rate to the minimum flow rate within the stated
accuracy rating.

Zero Elevation and Suppression: The range at which the zero value of the
measured variable is not at the lower range value.
Response Time: An output expressed as a function of time, resulting
from the application of a specified input (step) under specific
operating conditions.

Time Constant: This is a specific measure of a response time. It is the
time required for a first order system to reach 63.2% of the total
change when forced by a step.
Characteristic Curve (Input-Output Relationship): A
curve that shows the ideal value of an input-output
relationship at steady state.

Reproducibility: There should be a closeness         of
agreement among repeated measurements of            the
output for the same value of the input made under   the
same operating conditions over a period              of
time, approaching from both directions.

Noise: In process instrumentation noise is an unwanted
component of a signal or a process variable.
Control Valve
Flow Coefficient, CV - Is a capacity coefficient which is defined
as the number of U.S gpm of 60°F water which will flow
through a wide-open valve with a constant pressure drop of 1
psi across the valve.
Industrial process control
Current to Pressure Signal Converters, I/P
Analog to Digital, A/D, or Digital to Analog, D/A
Volume Booster
Valve Positioner
A valve positioner is a proportional-only controller whose main
function is to eliminate or minimize valve hysteresis
Valve Sequencing

The practical rangeability of a control valve is limited to
approximately 100/1 with most valves falling below 50/1. These
rangeability values are sufficient for most control applications.

In some applications however, such as pH, the rangeability
required may exceed 1000/1 and the control scheme must be
designed to satisfy this requirement in order to achieve good
control.

In split ranged or sequenced strategies, the controller's output
actuates more than one valve, typically two valves.
Process Modeled Through
 Dead Time And Capacity
DEAD-TIME-ONLY PROCESSES
Industrial process control
Steady State Gain (K) of Dead Time Process

The steady state gain of the dead-time element is the ratio of the
output amplitude to the input amplitude when both are time
invariant.
Capacity Processes Level Tank - Stores Mass
Capacity Processes Heater - Stores Energy
Non-self-regulating or integrating capacity (NSR)
A capacity is termed non-self-regulating when a change in the
controlled variable has no affect on the process load.
Industrial process control
Self-Regulating-Capacity or First-Order Lag

In the self-regulating-capacity process, load is not independent of
level. When level changes in this process the load also changes.
Self regulation always tries to restore equilibrium and achieve
steady state.
Industrial process control
This process operates as though it has a built-in automatic
controller that achieves steady state by making fi = fo. In fact we
would not need to control this process if the tank was very large
( ). Obviously, it is more practical to have a smaller tank and put
a control loop on it.
Interacting Capacities

Interacting capacities are identified as types of capacities in
which the downstream capacities affect upstream capacities. C3
affects C2 and C2 affects C1.
Non-Interacting Capacities

The non-interacting capacity can be identified as a capacity that
has no effect upstream i.e. C3 does not affect C2 and C2 does not
affect C1.
Input/Output Relationship
of Non-Interacting Capacity Processes
Input/Output Relationship
of Non-Interacting Capacity Processes
Input/Output Relationship
of Interacting Capacity Processes
Basic Control Modes And
Choice Of Controller Algorithm
INTRODUCTION

The effective control of a process in a feedback loop
depends on the correct choice of the controller mode
or algorithm required for the given application.

The controller algorithm is a mathematical expression
described as the PID consisting of proportional, integral
and derivative components.

Each of these PID components affects the response of
the loop and has certain advantages and limitations.
On-Off Algorithm

The simplest and most common type of control
mode, considering home applications.

Although there are multi-position discontinuous
controllers available in industry, generally On-Off control
refers to the two-position version.

A consequence of this is that under On-Off control the
loop never stabilizes.
Industrial process control
Industrial process control
Industrial process control
Application of On-Off Control

1) Processes where precise set point control, is not
required e.g. some level tanks; and processes such as
home heating, cooling or refrigeration.

2) Part of an emergency shutdown process (ESD). The
objective here is not regulatory control but safe
operation.

3) Large capacity processes having a low dynamic gain
and a potentially small (acceptable) amplitude of
oscillation.
Advantages and Limitations of On-Off Control

     Advantages                Limitations

   Extremely simple      Demand not balanced by
                                supply

Inexpensive controller      Loop always cycles

No tuning required for   More energy used by the
      start up                   valve

 Less expensive valves
Proportional Algorithm

Proportional control is the minimum controller
algorithm capable of balancing supply with the demand
of the process and achieving steady state.

A properly adjusted proportional controller can
eliminate the oscillations that are inherently part of
On-Off control.
Industrial process control
Assume initially that everything is balanced.

The inflow to the tank equals the outflow of the tank
at 50% and the process is in a steady state condition.

                   Fin = Fout = 50%
Also assume that at the 50% load (Fout) for this
particular tank:

Measurement = Set Point = 50%

                     c = r = 50%

If this condition persists, that is Fin = Fout @ 50%
load, and c=r, the operator does not need to take any
control action since the supply is already balanced by
the load.
Assume in this example that suddenly the load (Fout)
changes from 50% to 60%.

The first indication of the load increase will be a change
in the level of the tank.

Acting as a proportional controller, its task is to open
the supply valve in order to stop the level from
changing.

When a balance is achieved between the supply and the
demand such that Fin = Fout = 60%, the level stops
changing.
Unfortunately, at this new steady state condition, the
measurement is at a new value below the set point.

The error (r-c) is called offset. It is a steady state error
and is characteristic of all proportional controllers.

The magnitude of the offset depends on the size of the
load change and the capacity (size) of the tank.
Industrial process control
Industrial process control
The output of the proportional controller is proportional to the
input.
                               m = Ge
When the controller is switched to automatic its output goes to
zero since the error is zero.
                            m = G (r-c) = 0
As the output goes to zero the valve shuts, decreasing the Fin to
0% and causing the level to decrease. The level will stop
decreasing only when the supply balances the load. This balance
will occur only if Fin becomes 50% again.

If the process dictates that the gain of the controller should be 20
when controlling at 50% load. The controller will operate with a
2.5% error.
                            50 = 20 (2.5)
1. Proportional controllers always operate with an
   error.

2. The higher the controller gain, as dictated by the
   process gain, the smaller the error.


(It should be pointed that the controller gain can not be set
arbitrarily. It is dictated by the process gain and for a given loop
gain has a reciprocal relationship to the controller gain).
To accommodate zero error situations
                        m = Ge + Bias

The Bias term has a fixed value and does not have the ability to
change. The Bias is the output of the controller whenever the
error is zero.
                        m = Bias , if e = 0

Apply this algorithm to the previous example.
Assume that we put the controller in manual and adjust all the
signals to 50%: r = c = Fin = Fout = 50%. When we place the
controller in automatic:
                           m = Ge + Bias
                         m = 0 + Bias = Bias

A typical Bias setting being 50%, m = 50%
If the load changes an error will occur once again.
                           m = Ge + Bias
                          60 = 20(e) + 50
                             20(e) = 10
                              e = 0.5%

Some manufacturers write the expression
                    m = (100/PB) e + Bias

Proportional band is defined as the change in input required to
produce a full range change in output due to proportional control
action.

It may also be seen as the change in measurement required to
change the output 100% or to fully stroke the valve.
Different Proportional Bands and Gains
Proportional Offset
                      m = (100/PB)e + Bias

                 Offset = e = (m - Bias)(PB/100)

There are two conditions which can make the offset equal to
zero or a very small value.

1) Small values of PB or high gains on the controller. Remember
    that the process dictates the controller gain or PB. It is not
    an arbitrarily assigned value.
2) If (m = bias): in this situation, when the load is equal to the
Bias, there will be no offset. Since the Bias is fixed this implies
that the load is also fixed.
Open Loop Response
Closed Loop Response
Application of Proportional-Only Control
Proportional-only control is not a common control application.

1) Processes where precise control at the set point is not
   required. Processes where offset can be tolerated.

2) Processes where the load changes are infrequent (seasonal).
This allows matching load with Bias to eliminate or minimize the
offset.

3) Low gain processes. Typically these are large capacity
processes with low process gains. The low gain of the process
allows a high gain on the controller minimizing the offset.
Advantages and Limitations of
         Proportional-Only Control

     Advantages              Limitations

  Immediate response           Offset

     Easy to tune

Good period of response

        Simple
Integral Algorithm
The error in proportional algorithm could be eliminated if
the two terms in the parenthesis were made to equal each
other.
               Offset = e = (m - Bias) PB/100

Since the output of the controller m is directly related to the
load our only choice is to vary the Bias term by making the
Bias = m and thus eliminating the error.

The integral mode fulfills this requirement by providing the
variable Bias capability that automatically achieves this load
balancing task while eliminating errors at steady state.
mI=(1/I) edt + mo

                        mI = Ti edt + mo

where

I = min./rep
Ti = rep./min.

mI : is the output of the integral-only controller.

I : is the gain adjustment for the integral-only controller known
as the integral or reset time.

mo : is the controller output at the time integration starts
Open Loop Response
Closed Loop Response
Application of Integral-Only Control

Whenever the integral mode is required in an application it is
customary to have a small amount of proportional along with it.

The integral mode eliminates the offset at a cost of slower loop
response.

Integral can be justified and should be the major contributor for
the following applications.

1. Slow loops designed to produce slow corrective action.
2. The integral mode is the major contributor in fast flow control
   applications usually with a minor contribution from the
   proportional controller.
Windup



Saturation of the integral mode of a controller
developing during times when control cannot be
achieved, which causes the controlled variable to
overshoot its setpoint when the obstacle to control is
removed.
Advantages and Limitations
          of Integral-Only Control
      Advantages                   Limitations

   Eliminates offset          Slows the response

      Easy to tune            Potential windup or
                                  saturation

Reduces integrated error      Unstable with NSR
                           capacity. (Always oscillates
                                    with NSR)
Proportional Plus Integral Algorithm

The need for precise control with zero error at steady
state brought the integral mode in the picture.

The integral mode eliminated the error at steady state
but at an unacceptable cost of a slow loop response.

Combining the two modes in a PI controller is a very
effective compromise suitable for most process
applications.
The following observations should be made:

1) Integral mode is a must for precise control.

2) The cost of integration is a slower response.

3) If unable to eliminate the error at steady state the
potential exists for loss of control through what is
known as windup or saturation.
The PI is by far the most common algorithm used in
process control applications.

In most plants the PI controller is used in excess of 80%
of the time.

The reason for its popularity is due to the fact that the
algorithm benefits by getting an instantaneous response
due to error from the proportional mode and the
elimination of steady state error from the integral mode.
m = (100/PB) [e + (1/I) edt]
Open Loop Response of PI Controllers
Closed Loop Response of PI Controllers
Advantages and Limitations
                of PI Control

      Advantages                 Limitations

        No offset           More difficult to tune

 Can minimize integrated    Windup or saturation
         error                   potential

Reasonably good period of
       response
Derivative Algorithm

• In some applications the increased period of response
due to the integral mode is not acceptable

• Especially if we recognize that after an upset it takes
about 3 cycles for a loop to settle down and reach
steady state.

• Furthermore in approximately 10% of the processes
the natural period of the loop is rather long and the
penalty of even longer periods due to the need of
having integral is not desirable.
•The natural period of a distillation column is typically
several hours.

•If a given column has a natural period of 4 hours
and, assuming a penalty of a 50% longer period due to
the integral mode.

•It would take approximately 18 hours (4 x 3 x 1.5 = 18)
for this loop to reach steady state.

•The problem gets further aggravated if other upset(s)
occurs before steady state is reached.
Industrial process control
Open Loop Response (D Setting Fixed)
Proportional plus Derivative Algorithm


•Remember that derivative-only controllers do not
exist.

•The derivative mode must be combined with a
proportional or a proportional plus integral controller
and the phase will be limited to some value less than
+90%.
The older version with the Derivative on error

                m = 100/PB ( e + Dde/dt ) + Bias
The newer version with the Derivative on measurement

               m = 100/PB ( e - Ddc/dt ) + Bias
Application of Proportional
             plus Derivative Controllers

The proportional plus derivative controller is not a frequent
choice in process control applications.

Its major limitation is its inability to eliminate offset or
steady state error.

To apply the derivative mode we have to make sure that the
controlled variable is free of noise.
Regarding offset it has the same problem as the
proportional-only controller.

The addition of derivative however produces an
improvement in the speed of response.

PD controllers are recommended for large capacity
processes where precise (set point) control is not
required.

The major application of this controller is in batch
processes where because of the nature of the process
(integrating process) it may not be desirable to use the
integral mode.
Advantages and Limitations of PD
               Controllers

     Advantages                  Limitations

Good response period                Offset

Fastest to reach steady     Can not handle noise
          state

Easier to tune than PID   Insufficient benefit on fast
                                   processes
PID Algorithm




This three-mode controller has the attributes of all the
modes along with their limitations.

In summary the PID uses the immediate response of the
proportional mode followed by the integral mode's ability to
eliminate the offset.

The slowing down of the response due to integration is
compensated for by the derivative mode.
To justify the application of the PID controller the
process should satisfy the following conditions:

1. The controlled variable should be free of noise.

2. The process should have a large capacity for optimum
benefit.

3. The slower response due to the integral mode is not
acceptable for good control.
Summary of Closed Loop Responses
Advantages and Limitations of PID
                 Controllers

      Advantages              Limitations

Good period of response    Noisy measurement

Compensates for the slow    Difficult to tune
       integral

  Minimizes integrated      Windup concerns
         errors

 Optimizes control loops
Procedure for Determining
              Process Characteristics

1. Let the system stabilize.
2. Open the loop by placing the controller in manual.
3. Make sure the system is at steady state, the output
and the controlled variable maintaining their values.
4. Introduce a small disturbance by stepping up the
output of the controller.
5. Record the reaction of the controlled variable.
6. Bring the output back to the normal operating point
and switch to auto.
Industrial process control
Industrial process control
Steady State Gains
Steady State Gains of Elements

Steady state gain is simply the slope of the input-
output relationship of the element's response curve
when both the input and output are time invariant (do
not vary with time).
Industrial process control
Linearization For Constant Loop Gain


Instead of tuning at the highest gain condition to be on
the safe side, a better solution to the non-linearity
problem is to use a complementary linearizing element
in the loop through either the valve or other element.

The objective of good control is to make the loop gain
independent of the operating point as much as
possible.
Industrial process control
THE STEADY STATE GAIN OF
MEASURING ELEMENTS/TRANSMITTERS
Flow Transmitters
The most common industrial flow applications involve one of the
following measuring Devices.
           LINEAR DEVICES               NON LINEAR DEVICES



       Magnetic Flow Meters                   Orifice

    Positive Displacement Meters              Venturi

           Vortex Meters                   Flow Nozzle

          Turbine Meters                  Elbow Meters

             Ultrasonic                   Target Meters

            Rotameter                         Weirs

              Coriolis                        Flumes
Linearizing Differential Producers
Linearizing With A Compensating Response

It is possible to linearize the differential producer (orifice
plate) with a complementary response curve.

To find a curve (b) type function from one of the other
elements in the loop, i.e. the valve.

The advantage of this approach is the elimination of the
need for a square root extractor.

The disadvantage is that the loop will be operating with
(Flow)2 information.
Linearizing the Valve Characteristic
Industrial process control
Non-Linear Controllers
As electronic controllers were introduced, it was possible to
build non-linear PID controllers.

In some applications it is not desirable to have a constant
gain controller.

Non-linear controllers were designed to handle processes
with variable gain.

They were set up to have low gain in the high-gain region of
the process and high gain in the low-gain region of the
process.
Linearizing Process Characteristic with a
          Non-Linear Controller
Level Process
Linearizing a Non-Linear Process - Non-
             Uniform Tank
Heat Exchanger Process
Linearizing Processes Whose Gain Varies
           Inversely With Load
Tuning Feedback Control Loops
Acceptable Tuning Criteria Used in the
          Process Industry
• If safety is the primary concern, speed and efficiency
can be sacrificed and a critically damped response might
be the best choice.

• If the objective is to eliminate the error and achieve
steady state as quickly as possible after an upset, then
some form of underdamped response will be the choice.

Generally most of the better tuning techniques lead to
an underdamped response, with some decay ratio and a
specific speed of response (period.)
Tuning Criteria Using
         Error Minimization Approaches



The objective of a well-tuned loop is to eliminate the
error as quickly as possible by bringing the
measurement equal to the set point.
Quarter Amplitude Decay Criteria
(QAD) is one of the most common under-damped response
criteria.

The controller gain is adjusted so that the amplitude of each
successive cycle is one quarter of the previous amplitude.

Unfortunately, this criteria does not completely define the
response.

Beyond an amplitude decay ratio, it gives no other
information as to what the optimum period of the response
should be.
There is no mathematical justification for the QAD response. Its
popularity and acceptance are due to its open loop gain, which
between 0.5 and 0.6 seems to be a reasonable compromise in
damping and period.
The main criticism of QAD as a criterion is that it gives no
information about speed of response, or period of a
loop, and as such, it does not indicate an optimum
response.


In two or three mode controllers such as PI or PID there
are an infinite number of settings that will give you a
QAD response, only one of which will have the correct
period for optimum response.
Tuning Criteria Using Integral Error
                    Minimization
These techniques are especially useful if energy is used to make
the product.

Minimization of the area (error) under the curve leads to less
energy consumption and higher efficiency.

There are various error minimization criteria, each having certain
advantages and limitations, and different PID settings.
Integrated Error (IE)

                            IE = e dt

Integral Absolute Error (IAE)

                           IAE = e dt

Integrated Squared Error (ISE)

                           ISE = e2 dt

Integrated Time Absolute Error (ITAE)

                          ITAE = e t dt
Robustness

•A loop tuned to particular criteria raises the question of
loop stability when process conditions change.


• A robust control loop, has a safety factor built in to the
controller tuning settings, allowing the loop to maintain
stability even if the process undergoes moderate
changes in gain or dead time.
• A robustness plot allows an analysis of how safely a loop is
tuned.

   The gain ratio is the ratio of the current process gain to the
   original process steady-state gain.
   The delay ratio is the ratio of the process dead time to the
   dead time existing when the process was tuned.
Making PID Adjustments and Observing their
         Effect on Loop Response
Proportional Band or Gain Adjustment
To change the response of the loop, adjust only with:
PB or Gain. Decrease the loop gain to less than one in
order to dampen the response.


The obvious choices of response for this controller
would range from an overdamped response to a
Quarter Amplitude Decay response (QAD).

To get a QAD response the Proportional Band would
have to be doubled (2 x PBu) to drive the loop gain to
0.5.
Industrial process control
The proportional band or gain adjustment can be
summarized as follows:

  • Changing gain or PB affects only the damping of
  the response.

  • Increasing the PB setting decreases gain while the
  period stays roughly the same.
Any change of period length over n is of minor
consequence. The amount depending on the process
characteristics.

•For dead-time only processes there would be no period
change at all.

•For dead-time plus capacity processes the period might
increase by 10 - 15% over the natural period n.

It is best to consider the proportional adjustment as a
gain adjustment with no significant effect on the period
of response.
PI Adjustment
PD Adjustment
PID Adjustment

Suppose we find our damping to be acceptable, but
the period of response, o is too long.

We need to maintain our loop gain constant, but to
either increase derivative action or decrease integral
action.

Changing either one alone will not only change o, but
will also change the gain vector which will in turn
affect loop gain.
The correct procedure in this case would be to increase
derivative gain GD, by increasing derivative time D,

while at the same time to decrease integral gain GI by
increasing integral time I.

This will tend to increase derivative action while
maintaining the length of the PID vector constant.

As a result, damping will remain unchanged while
response period o is decreased.
Interacting And Noninteracting PID
There are at least two ways in which three-mode PID
controllers can be built.

The PID algorithm discussed so far is an ideal noninteracting
controller algorithm.

The noninteracting controller is designed such that its
derivative and integral modes are in a parallel path and act
independently of each other.

The interacting PID controller is designed such that the
integral and derivative modes interact.
Industrial process control
Industrial process control
Effective PID values in terms
    of the actual settings
Reasons for Tuning Methods


Over the years many tuning methods or approaches
have been developed and used with varying degrees of
success.


There is no general agreement as to what method is the
best to use, the preferred choice usually being the
one, that the individual has the most experience with.
• Some of the methods are trial and error solutions to
finding the desired response; others rely on
mathematical relationships.

• The preferred tuning method might be, it is desirable
to have the capability to apply more than one approach.

• In some cases, process or operational constraints
dictate the method to use.

• With experience, you develop a feel of what approach
works best for a given application, and tune accordingly.
Keep in mind that any tuning method, will give you only
preliminary settings, which require fine tuning later for
optimum response.

The various tuning methods can be grouped into closed-
loop and open-loop categories.
The main distinction between the two is as follows:

   •In the closed-loop methods, adjustments are made
   and tested with the controller in automatic.

   •In the open-loop methods, preliminary settings are
   calculated by an open loop test, with the controller in
   manual. These preliminary adjustments are
   introduced in the controller and tuning is continued
   with the controller in automatic.
Summary of making PID adjustments and
  observing their effect on loop response




The table is designed to assist the user in deciding which direction the adjustments should be made.
Procedure for Trial and Error
            Constant Cycling Method
                  P-Only Controller
1. Place controller in manual.
2. Increase proportional band to a safe wide value
3. Place controller in automatic.
4. Make a 5 - 10% set point change around the operating
   point.
5. Reduce PB until constant amplitude cycling occurs.
6. Double PB for QAD. Controller is tuned.
7. Make a small upset and observe the response.
   Measurement will not be at set-point at steady state.
P + I Controller

1. Increase I-time to maximum min/rep or minimum rep/min.
   (This eliminates the integral action.)
2. Tune as a P-Only Controller.
3. Increase Integral gain until constant amplitude cycling
   occurs.
4. Double the I-time in min/rep for QAD. (Halve the I-time if
   in rep/min.)
5. Make upset and observe the response. Measurement
   should reach set-point at steady state.
PID Controller (Interacting Types)

1. Adjust the integral time min/rep and proportional band to high
values.
2. Adjust derivative time to a very low value.
3. Reduce PB until constant amplitude cycling just occurs.
4. Double PB for QAD.
5. Controller is now tuned as P-Only.
6. Increase derivative time until constant amplitude cycling occurs.
7. Cut derivative time by 1/2 for QAD.
8. Set integral time to a value of 2 to 4 times that of the derivative
time.
9. Make upset and observe the response. Measurement should be
at the set-point at steady state.
10. Readjust PB, I, and D small amounts to get desired response.
Procedure for Ziegler-Nichols and Cohen-Coon
       Constant Amplitude Cycling Method
1. With the controller in manual, remove the Derivative and
   Integral modes. (Remove or turn off Derivative action. Set
   Integral to its lowest gain value, by setting to maximum
   min/rep or minimum rep/min.) Set the Proportional Band or
   gain to a safe value depending on the process.

Examples of safe values of PB or Gain:
      · Flow PB 300-500 % or Gain 0.2 to 0.3
      · Temperature PB 100 % or Gain 1.0

At this point, you have a low-gain, Proportional-only controller.
2. Switch the controller to automatic, put a small upset by
introducing a 5-10% set-point change around the operating point
and observing the response. You should get a safe sluggish
response.

3. Increase the gain or decrease the Proportional Band and repeat
step (2) until uniform or sustained oscillations occur as shown in
curve (C). If the gain is too low such as curve (A) increase the gain
or lower the PB. Avoid unstable responses such as curve (B). Record
the following information at uniform oscillation. Make sure the
oscillation is due to the loop gain and not due to a limit cycle. (e. g.,
Valve hitting the stops produces what looks like uniform oscillation
but the gain > 1).
Industrial process control
Industrial process control
Procedure for Obtaining a Process Reaction Curve
and Optimum PID Settings from Ziegler-Nichols or
     Cohen-Coon Process Reaction Method
1. Let the system stabilize at the normal operating point (set point
and load at normal.)
2. Open the loop by placing the controller in manual. The output
should hold at the same value as in step (1).
3. Make sure the system is at steady state with the output and the
controlled variable maintaining their values.
4. Introduce a small disturbance by stepping up the output of the
controller. The resulting output change should have enough
resolution for analysis.
5. Record the reaction of the controlled variable. This is where a
fast speed recorder at the output of the transmitter (in the order 1
in./min) comes in handy.
6. Bring the output back to the normal operating point and switch
controller back to auto.
After obtaining the Process Reaction Curve, proceed to determine
P, PI, or PID settings using either Ziegler-Nichols or Cohen and Coon
equations as shown.
Industrial process control
Procedure and Summary of Integral Criteria-
            Driven Open-Loop Method
Obtain a process reaction curve
Industrial process control
Cascade Control
•If the load (Fw) suddenly increases, the temperature (T2)
decreases.
•The controller senses this and acts on this error through its
algorithm.
•In two to three cycles, the loop stabilizes.
Industrial process control
Cascade Control may be defined as, "control in which the output
of one controller is the set point for another controller."




The set point to the flow controller defines the amount of flow
required. On an upset in flow, the controller repositions the valve
to bring the flow to the set point, r.
These cascade loops are known as the primary and
secondary loops.

The loop closest to the controlled variable is the primary
loop and the loop manipulating the valve is the secondary
loop.

The primary loop is known also as the master loop, outer
loop, or the slower loop.

The secondary loop may be called the slave loop, the inner
loop, or the faster loop.
The purpose of cascading is to have the secondary loop
compensate for any supply upsets that may occur
before they can influence the primary controlled
variable.


A supply upset to the primary loop is in effect a load
upset to the secondary loop, and a fast-acting
secondary can immediately correct for it.
Industrial process control
Industrial process control
Industrial process control
Results and Considerations



In order for the cascaded control scheme to function
without adversely affecting the gain of the primary loop,
The 1/ 2 ratio must exceed 4.

The higher the ratio, the easier it is to cascade.
Advantages of Cascade
1. Cascade control eliminates the effects of supply upsets.

2. Quicker return to set point in the primary loop and less
integrated absolute error (IAE).

3. The secondary loop is more responsive to the demands of
the primary.

4. The primary loop sets the amount of supply input rather
than valve position. Thus, the effects of valve characteristics
(including non-linearities) are minimized, and effectively
removed.
Limitations of Cascade
1. More expensive because of additional hardware needs.

2. The primary loop must be substantially slower than the
secondary loop.

3. In some applications it is difficult to break the process into
a primary and secondary loop and identify the supply
variable.

4. Compared to a feedback loop, it is more difficult to start up
and tune a cascade loop.
Specific Cascade Applications
Valve Positioner
The primary reason for having a positioner is to remove hysteresis
from the valve.
Limit Cycling

Limit cycling can be another consequence of hysteresis, or dead
band. The limit cycle is a clipped sine wave of the manipulated
variable. Controller adjustments (tuning) cannot eliminate these
oscillations. Widening PB will increase the amplitude and the
period of oscillation, while decreasing integral action reduces
amplitude and increases the period.




Recognizing a limit cycle wave (clipped sine wave) can eliminate
some frustrating and unsuccessful tuning effort. The only solutions
to a limit cycle are as follows:
• Use a valve positioner or other cascade application.
• Remove integral action from the controller.
Temperature On Flow Cascade Control

Temperature on flow is a good candidate for cascade control. The
supply is well defined and the flow and temperature processes
have significantly different natural periods allowing a good cascade
within the natural period ratio criteria.
Temperature-On-Temperature Cascade Control Of An Exothermic
Reactor




The idea here is to keep the temperature inside the reactor (T1) at
the desired value by controlling the temperature of the jacket (T2)
by manipulating cooling water flow to the jacket.
Flow as the Inner Loop

The secondary loop is frequently a flow loop as seen in
the various temperature cascades.

The benefits are that the flow loop protects the primary
loop from supply upsets;

overcomes non-linear valve characteristics;

and, reduces the effect of valve friction on the primary
controlled variable.
Level on Flow (Valve Positioner) Cascade

A level application requiring precise control and unable
to attain it due to valve hysteresis or frequent supply
upsets.

It is a good candidate for level valve position cascade.

A cascade through either a valve positioner or a flow
loop can be used since the level loop (primary) is most
likely four times slower than the valve position loop, so
that the criteria 1/ 2 > 4 is not violated.
Integral Windup Preventing Measures in Cascaded
Loops

If in attempting to eliminate a sustained error, the
controller output goes beyond 0 to 100%, the controller
is wound up.

Windup occurs if the error persists, with the valve fully
open and the controller output at 100%.

The controller becomes saturated, with loss of control.
Industrial process control
Windup Prevention Measures

Place controller in manual.

The operator can intervene to get any controller
(analog on digital) out of the windup state by putting
it in manual.

This is a simple solution, but not practical in most
applications.

Sooner or later this approach fails.
Tuning Cascade Loops
Pre-Startup Check
1. Place the primary controller in manual and the secondary
   controller to the local set point.

2. Tune the secondary controller as if it were the only control
loop present.

3. Return the secondary controller to remote set point and
place the primary controller in auto.

4. Now tune the primary loop as if it were the only control
loop present.

Remember, when tuning the primary controller that there
should be no interaction between the primary and secondary
loops.
Feedforward Control
Feedback Loop Advantages
• Does not require extensive knowledge of the process.

• Easy to implement (start up and tune).

• Requires minimal amount of hardware (least
expensive control strategy.)

• Can be successfully implemented most of the time.
(Feedback is sufficient 80 -90 % of the time.)

• Reasonably good control.
Feedback Loop Disadvantages
• Process characteristics dictate the response.

• Response is oscillatory.

• Cannot handle frequent load upsets.

• Trial and error solution to valve position consumes
more energy.
If in addition to the load upsets the process was also
subject to frequent supply upsets, cascade control was
the solution.
Feedforward or calculation control is the alternative
control strategy when we are unwilling or unable to
accept an oscillatory type of response in a given
application, or if the load upsets are very frequent (<
3 n) the controlled variable does not have a chance to
settle out.
Industrial process control
Feedforward Advantages
• Can handle processes with frequent load upsets (< 3tn).

• Potentially perfect control without oscillations.

• Response virtually independent of process
characteristics.

• Minimum integrated errors (IE, IAE) can approach zero.

• Avoiding a trial error search of valve position conserves
energy.
Feedforward Disadvantages
• Requires more knowledge of the process.

• Requires additional engineering effort and time.

• Requires additional hardware for implementation.

• More expensive than feedback control.

• Economic justification to implement feedforward is made
conditionally.
Feedback Trim Loops

The feedforward model attempts to predict the effect of
steady state and dynamic loads on the product being
made.

It is not feasible to include all the loads that affect the
product, in order to have a perfect feedforward model.

It is impossible to come up with a perfect feedforward
requiring the need to have a corrective feedback loop
known as the feedback trim loop.
Industrial process control
Mass Flow Processes




                      @ S.S. LEVEL = CONSTANT
as                              dh/dt = 0
Thus the steady state calculation in this example will simply make the
flow input equal to the flow output.
                           @ S.S. Fin = Fout
Therefore
                              Fin = Fout
Level Tank Application
Applying Feedback Trim Loop
  to Tank Level Application
Single Element Drum Level
        Application
•For negative feedback, an odd number of reverse-acting
elements is needed.

•The final actuator, process and transmitter are all direct-acting
elements.

•The controller is put in a reverse-acting mode for negative
feedback.
•In open-loop test to check, it is found that as the steam flow
or load increases, the level in the drum initially increases
(instead of decreasing as expected.)

•Typically, the level will go up initially and then come down as
shown, temporarily creating a positive feedback situation and
loss of control.

•This happens because as the load increases due to more
steam flow, the pressure in the drum decreases, causing the
liquid in the drum to temporarily increase or swell.
Industrial process control
Two-Element Feedforward
              Drum Level Application
•During steady state operation the steam flow (load)
information is used to control the feed water flow on a
pound-to-pound basis responding immediately to any
load changes.
•The drum-level feedback trim loop provides the
necessary slow corrections to bring measurement back
to the set point.
•This configuration assumes a linear and repeatable
relationship between the load and the feed water valve.
•If this is true then two-element control is sufficient.
Industrial process control
Three-Element Feedforward
  Drum Level Application
Energy Flow
              Feedforward Applications

• Energy flow processes vary in their complexity.

• These processes must be sufficiently well defined
before attempting feedforward control.

• For a given process there may be several loads that
affect the product from the steady state point of view.
• Some of these load contributions are nonlinear and in
some cases difficult to evaluate and implement in the
model.

• These are the type of processes that consist of multiple
lags and long dead-times which make them difficult to
control with a feedback loop and thus good candidates
for a feedforward strategy.
Simple Energy Flow Example




•To implement this in a feedforward loop, measure Qout and put
an equal amount of Qin.
•If succeed, the temperature in the vessel will stay constant.
Heat Exchanger Energy Flow Example
Recognize that this equation is:

1.   Steady state without any dynamic considerations.

2. Only the major loads are represented in the model.

3. Minor loads are not accounted for. These include:
    • losses to ambient,
    • measuring element and transmitter accuracy,
    • change in efficiency due to fouling (scaling) or change in operating point,
    • heat lost in condensate.

4. Supply variations relating to the energy of the steam (enthalpy) are not
accounted for. This might dictate cascade for supply upsets, not uncommon in
this type of application.
Industrial process control
Industrial process control
Applying A Feedback Trim Loop To
        The Feedforward
Trim Loop Characteristics:

• Use a P + I controller tuned for a slow response, no
QAD.

• Typical settings require wide proportional bands (low
gain) and relatively long integral times in min/rep (i.e. 2-
5 min/rep), no derivative action.

• The idea is to take slow corrective action without
affecting the major feedforward scheme.

• Do not introduce non-linear elements that affect the
gain versus operating point relationship of the loop.
• Remember, if unable to linearize for constant loop
gain, tune at the highest gain, sluggish response is
acceptable in this case.

• If the feedforward model is reasonably accurate, the
trim controllers output should be 50% during normal
operation.

• If this is not the case, i.e., output of trim either high or
low, there is a good chance that the model does not
accurately represent all major loads.
Ratio Control
Ratio Control Scheme

• Ratio is a rudimentary form of feedforward where one
variable is controlled in ratio to another.

• It is used in processes where two components are
mixed together in a certain proportion or ratio.

• The controlled variable in effect is the ratio.
Industrial process control
Simple Ratio Example
Ratio Controller Application
Adding Feedback Trim
Selective Control
Industrial process control
Median Selectors
The typical applications of selector systems can
be categorized as follows:

• Protection against instrument failure

• Control through most critical measurement

• Protection of equipment (safety)
Protection Against Instrument Failures




                Furnace Pressure Measurement Protection
Exothermic Reactors
Control Through Most Critical
        Measurement
Protection of Equipment (Safety)

Parallel Metering Combustion Scheme

In boiler applications the furnace control system must
satisfy various needs:

•Maintenance of safe furnace conditions
•Maintenance of safe furnace pressure in balanced
draft units
•Satisfaction of the energy demand
•Maintenance of correct air/fuel ratios
Industrial process control
Pumping Station On a Pipeline

The system should provide protection against the following:

• Cavitation. If the suction pressure drops below a
predetermined low value, the valve starts closing to bring
suction pressure up and avoid cavitation.

• Motor Load. As the motor draws a current exceeding the
motor specifications, the valve starts closing to protect the
motor.

• Downstream Pressure. If the discharge pressure attempts to
exceed the maximum recommended downstream pressure, the
valve closes to prevent overpressurizing process piping.
Industrial process control
Tuning Selective Loops

• Tune each loop and testing the system for
functionality.

• When all loops     are   tuned,   check   scheme
performance.

• Control should alternate smoothly, without a
"bump," automatically transferring from one
controller to another through the selective system.
Adaptive Control
•The word adapt means to change or fit by modification to new
conditions.

•An adaptive control system may be defined as a system whose
parameters automatically change in response to changing process
characteristics.

•The automatic change of the control parameters allows
compensation for the changes in the process characteristics and
the maintenance of a constant loop gain.

•A simple linearization to achieve constant steady state is not
considered adaptation since all the controller functions remain the
same.
•A nonlinear controller typically used in a pH application
operates at different gains based on the loop operating point.

•This controller is not considered adaptive since its controller
functions are fixed.
•If the titration curve drifts (changes shape) the linearization loses its
effectiveness and there is nothing the controller can do to take care of the
problem.
•Therefore, this is strictly nonlinear control. Remember, to be adaptive, the
controller must change its parameters in order to accommodate the
changing process parameters.
•To accomplish this requires a more capable controller as well as additional
communication between the process and the controller.
Approaches to Adaptation

A few approaches have been used to implement
adaptive control strategies:

• Gain scheduling or programmed adaptation - based
on a change in a process variable i.e. the set point.

• Feedforward adaptation - based on a change in load.

• Feedback adaptation - based on a change in the
controlled variable (measurement.)
Industrial process control
Example of Programmed Adaptation Using
     Process Variable Information
Industrial process control
Industrial process control
Multivariable Control
Industrial process control
Industrial process control
Process Equations:

                     C1 = K11g11m1 + K12g12m2
                     C2 = K21g21m1 + K22g22m2

Changing m1 affects both C1 and C2.
Changing m2 affects both C2 and C1.
Industrial process control
Simultaneous Control of Pressure and Flow




•This involves the simultaneous control of pressure and flow with the
fact that both valves affect both the flow and the pressure.

•The first consideration is to decide which valve should be assigned to
control a particular variable.

•The second consideration is whether a control system can be designed
to cancel the interaction between two loops.
Control Blocks
AI - Analog Input

The Analog Input block takes the input data from the Transducer block, selected by
channel number, and makes it available to other function blocks at its output.




266
DI - Discrete Input

The DI block takes the manufacturer’s discrete input data, selected by channel
number, and makes it available to other function blocks at its output.




267
PUL – Pulse Input

The Pulse Input Block provides analog values based on a pulse (counter) transducer input.
There are two primary outputs available. An accumulation output is intended to be
connected to an integrator block for differencing, conversion, and integration. This is most
useful when the count rate is low relative to the block execution rate. For high count
rates, the accumulated count of pulses per block execution can be interpreted as an
analog rate (vs. accumulation) value and can be alarmed.




 268
PID - PID Control

The PID block offers a lot of control algorithms that use the Proportional, integral and
derivative terms.




 269
EPID – Enhanced PID Control

The EPID block has all parameters of the PID block. Additionally it provides 4 types for
bumpless transference from Manual mode to Auto mode, and also a special treatment
for tracking outputs.


APID – Advanced PID Control

The advanced PID function block provides the following additional features comparing
to the standard PID algorithm and the enhanced PID:

• Selection of the terms (proportional, integral, derivative) calculated on error or
process variable
• PI Sampling algorithm
• Adaptive gain
• Configurable Limits of anti reset wind-up
• Special treatment for the error
• Discrete output to indicate the actual mode



 270
ARTH - Arithmetic

The ARTH block can be used in calculating measurements from combinations of signals
from sensors. It is not intended to be used in a control path, so it does not support
cascades or back calculation. It does no conversions to percent, so scaling is not
supported. It has no process alarms.




 271
SPLT-Splitter

The Splitter block provides the capability to drive multiple outputs from a single
input, usually a PID. This block would normally be used in split ranging or sequencing of
multiple valve applications. Included in the block features are the capability to open
valves as part of a predetermined schedule and leave open or closed a given valve after
the controller has transitioned off the valve. The splitter supports two outputs. Since this
block will participate in the control path after a PID block, back calculation support is
included.




 272
CHAR - Signal Characterizer

•The block calculates OUT_1 from IN_1 and OUT_2 from IN_2, according to a curve
given by the points:
                        [x1 ;y1 ], [x2 ; y2 ]..............[x21 ; y21]
Where x corresponds to the Input and y to the Output.

•OUT_1 is related to IN_1 and OUT_2 is related to IN_2 using the same curve, but there
is no correlation between IN_1 and IN_2 or between OUT_1 and OUT_2.




 273
INTG – Integrator

•The Integrator Function Block integrates a variable in function of the time or
accumulates the counting of a Pulse Input block. The integrated value may go
up, starting from zero, or down, starting from the trip value (parameter SP). The block
has two inputs to calculate flow.
•This block is normally used to totalize flow, giving total mass or volume over a certain
time, or totalize power, giving the total energy.




 274
OSDL - Output Signal Selector and Dynamic Limiter

The output signal selector and dynamic limiter block (OSDL) provides two different
algorithms types.
•As Output Selector the cascade input may be routed for one of two outputs based on
the value of the OP_SELECT input parameter.
•As Dynamic Limiter the cascade input is transferred to both output, but it is limited by
the secondary inputs multiplied by a gain, plus a bias. The Dynamic LIMITER is extremely
useful in one of its most important applications: combustion control with double cross
limits.




 275
FMTH – Flexible Mathematical Block

This block provides mathematical expression execution with inputs, outputs and
auxiliary variables generated by the user, and also including conditional expressions.
The FMTH block has the following characteristics:
• It allows execute several mathematical expressions “customized” by user with input
and output values, and also using auxiliary variables in these expressions.
• Friendly edition of the mathematical expressions, similar to the Microsoft Excel.




276
• It allows the usage of the following operations described in the table below:




 277
AO - Analog Output

The Analog Output Block is a function block used by devices that work as output
elements in a control loop, like valves, actuators, positioners, etc. The AO block receives
a signal from another function block and passes its results to an output transducer block
through an internal channel reference.




 278
DO - Discrete Output

The DO block converts the value in SP_D to something useful for the hardware found at
the CHANNEL selection.




  279
280
281
282
283
284
285
WorkShops

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Industrial process control

  • 3. Process It Is defined as: • Physical or chemical change of matter. • Energy conversion e.g., change in pressure, temperature, speed, electrical potential, etc. A process in a collection of vessels, pipes, fittings, gauges etc., is built for the purpose of producing a product or group of products.
  • 4. Process Control The regulation or manipulation of variables influencing the conduct of a process in such a way as to obtain a product of desired quality and quantity in an efficient manner.
  • 5. Input to Process: Mass or energy applied to the process. Output of Process: The product delivered by the process. This is a dynamic variable. Supply: Source of mass or energy input to process. Control Valve: Consists of the final actuator and final controlling elements. This is the forward controlling element which directly changes the value of the manipulated variable. Load: Anything that affects the value of the controlled variable under a constant supply input.
  • 6. Open Loop: Control without feedback. Open loop can not cope with load upsets. Example of open loop: automatic dishwasher, automatic water sprinkling system, a control loop with the controller in manual. Primary Element: The measuring element that quantitatively converts the measured variable energy into a form suitable for measurement. Transmitter: A transducer which responds to a measured variable by means of a sensing element, and converts it to a standardized transmission signal which is a function only of the measured variable.
  • 7. Controlled Variable: A variable the value of which is sensed to originate a feedback signal. (Also known as the process variable.) Controller: A device which operates automatically to regulate a controlled variable. Controller Algorithm (PID): A mathematical representation of the control action to be performed. Set Point: An input variable which sets the desired value of the controlled variable.
  • 8. Error: In process instrumentation, the algebraic difference between the real value and ideal value of the measured signal. It is the quantity which when algebraically subtracted from the indicated signal gives the ideal value. Manipulated Variable: A quantity or condition which is varied as a function of the algebraic error signal so as to cause a change to the value of the directly controlled variable.
  • 9. Feedback Control: Control action in which a measured variable is compared to its desired value to produce an actuating error signal which is acted upon in such a way as to reduce the magnitude of the error. Cascade Control: Control in which the output of one controller is introduced as the set point for another controller. Feedforward Control: Control action in which information concerning one or more conditions that can disturb the controlled variable is converted, outside of any feedback loop, into corrective action to minimize deviations of the controlled variable.
  • 13. Open Loop Control The operator walked up and down a plant, looking at gauges and opening and closing valves is effective only at the time when the operator moves the valve. At that instant the loop is closed. Open loop control works only when the load(s) on the process are constant. Any load change or supply upset can affect the product quality.
  • 14. Advantages of Closed Loop Control Increased productivity: Automatic closed loop control allows the amount of products made in a particular process to be maximized. On Spec Products: Industrial products are produced to meet certain purity levels. Energy and Material Conservation: A closed loop control application minimizes the amount of material and energy used in production. Safety: Closed loop control is the first line of defense before Emergency Shutdown Devices (ESD) override regulatory control devices.
  • 15. Types of Control • Continuous Control is used on continuous processes. A continuous process is one in which process material is continually flowing through the process equipment. • Sequential is often referred to as on/off control. It is a series of discrete control actions performed in a specific order or sequence. • Batch control is a combination of sequential and continuous control. A batch process is a process where the operation is time-dependent and repeatable.
  • 16. Positive Feedback •It can be defined as the control action in which the error is reinforced until a limit is eventually reached. •This obviously is not a desirable outcome of control action and should be avoided. •Imagine a tank in which level is being controlled. When the level exceeds the set point, the control action will increase the level further until the tank overflows.
  • 17. Negative Feedback •It can be defined as the control action in which the error is minimized, made as small as possible, depending on the algorithm of the controller. •This obviously is a desirable outcome of the control action and should be achieved in all feedback loops.
  • 18. Direct Acting Element is one in which the value of the output signal increases as the value of the input signal increases.
  • 19. Reverse Acting Element is one in which the value of the output signal decreases as the value of the input increases.
  • 20. Control Valves A control valve consists of a valve connected to an actuator mechanism. The actuator, in response to a signal from the controlling system, can change the position of a flow- controlling element in the control valve. The action of the final actuator is the first choice and is based on “Fail-Safe Control Valve Action”. (open, closed, and in place).
  • 23. Transmitters It can be set up (calibrated) as either direct acting or reverse acting.
  • 24. Processes It can be either direct or reverse acting. Most processes are direct acting. Energy Flow Process 1.Heat Exchanger 2.Refrigeration Mass Flow Process 1. Level Tank 2. Pipe Flow
  • 29. Rule for Achieving Negative Feedback To achieve negative feedback in a control loop you must have an odd number of reverse acting elements in the loop.
  • 30. The odd number of reverse-acting elements for negative feedback can be determined through an open loop test, conducted in the following manner. Place the controller in manual (open loop), and step up the output of the controller (5-10%) and observe (record) the output of the transmitter.
  • 32. Control Loop Elements And Their Contribution To Loop Performance
  • 34. Accuracy (Error) = Precision Error + Bias Error
  • 35. Range: The region between the limits within which a quantity is measured is the range of that measurement. Span: The measurement span is the algebraic difference between the upper and lower range values. Minimum Span : The minimum span of measurement that the primary element can be used to measure within its accuracy rating. Maximum Span: The maximum span of measurement that the primary element can be used to measure within its accuracy rating. Rangeability (Turndown): In flow applications, rangeability is the ratio of the maximum flow rate to the minimum flow rate within the stated accuracy rating. Zero Elevation and Suppression: The range at which the zero value of the measured variable is not at the lower range value.
  • 36. Response Time: An output expressed as a function of time, resulting from the application of a specified input (step) under specific operating conditions. Time Constant: This is a specific measure of a response time. It is the time required for a first order system to reach 63.2% of the total change when forced by a step.
  • 37. Characteristic Curve (Input-Output Relationship): A curve that shows the ideal value of an input-output relationship at steady state. Reproducibility: There should be a closeness of agreement among repeated measurements of the output for the same value of the input made under the same operating conditions over a period of time, approaching from both directions. Noise: In process instrumentation noise is an unwanted component of a signal or a process variable.
  • 39. Flow Coefficient, CV - Is a capacity coefficient which is defined as the number of U.S gpm of 60°F water which will flow through a wide-open valve with a constant pressure drop of 1 psi across the valve.
  • 41. Current to Pressure Signal Converters, I/P
  • 42. Analog to Digital, A/D, or Digital to Analog, D/A
  • 44. Valve Positioner A valve positioner is a proportional-only controller whose main function is to eliminate or minimize valve hysteresis
  • 45. Valve Sequencing The practical rangeability of a control valve is limited to approximately 100/1 with most valves falling below 50/1. These rangeability values are sufficient for most control applications. In some applications however, such as pH, the rangeability required may exceed 1000/1 and the control scheme must be designed to satisfy this requirement in order to achieve good control. In split ranged or sequenced strategies, the controller's output actuates more than one valve, typically two valves.
  • 46. Process Modeled Through Dead Time And Capacity
  • 49. Steady State Gain (K) of Dead Time Process The steady state gain of the dead-time element is the ratio of the output amplitude to the input amplitude when both are time invariant.
  • 50. Capacity Processes Level Tank - Stores Mass
  • 51. Capacity Processes Heater - Stores Energy
  • 52. Non-self-regulating or integrating capacity (NSR) A capacity is termed non-self-regulating when a change in the controlled variable has no affect on the process load.
  • 54. Self-Regulating-Capacity or First-Order Lag In the self-regulating-capacity process, load is not independent of level. When level changes in this process the load also changes. Self regulation always tries to restore equilibrium and achieve steady state.
  • 56. This process operates as though it has a built-in automatic controller that achieves steady state by making fi = fo. In fact we would not need to control this process if the tank was very large ( ). Obviously, it is more practical to have a smaller tank and put a control loop on it.
  • 57. Interacting Capacities Interacting capacities are identified as types of capacities in which the downstream capacities affect upstream capacities. C3 affects C2 and C2 affects C1.
  • 58. Non-Interacting Capacities The non-interacting capacity can be identified as a capacity that has no effect upstream i.e. C3 does not affect C2 and C2 does not affect C1.
  • 62. Basic Control Modes And Choice Of Controller Algorithm
  • 63. INTRODUCTION The effective control of a process in a feedback loop depends on the correct choice of the controller mode or algorithm required for the given application. The controller algorithm is a mathematical expression described as the PID consisting of proportional, integral and derivative components. Each of these PID components affects the response of the loop and has certain advantages and limitations.
  • 64. On-Off Algorithm The simplest and most common type of control mode, considering home applications. Although there are multi-position discontinuous controllers available in industry, generally On-Off control refers to the two-position version. A consequence of this is that under On-Off control the loop never stabilizes.
  • 68. Application of On-Off Control 1) Processes where precise set point control, is not required e.g. some level tanks; and processes such as home heating, cooling or refrigeration. 2) Part of an emergency shutdown process (ESD). The objective here is not regulatory control but safe operation. 3) Large capacity processes having a low dynamic gain and a potentially small (acceptable) amplitude of oscillation.
  • 69. Advantages and Limitations of On-Off Control Advantages Limitations Extremely simple Demand not balanced by supply Inexpensive controller Loop always cycles No tuning required for More energy used by the start up valve Less expensive valves
  • 70. Proportional Algorithm Proportional control is the minimum controller algorithm capable of balancing supply with the demand of the process and achieving steady state. A properly adjusted proportional controller can eliminate the oscillations that are inherently part of On-Off control.
  • 72. Assume initially that everything is balanced. The inflow to the tank equals the outflow of the tank at 50% and the process is in a steady state condition. Fin = Fout = 50%
  • 73. Also assume that at the 50% load (Fout) for this particular tank: Measurement = Set Point = 50% c = r = 50% If this condition persists, that is Fin = Fout @ 50% load, and c=r, the operator does not need to take any control action since the supply is already balanced by the load.
  • 74. Assume in this example that suddenly the load (Fout) changes from 50% to 60%. The first indication of the load increase will be a change in the level of the tank. Acting as a proportional controller, its task is to open the supply valve in order to stop the level from changing. When a balance is achieved between the supply and the demand such that Fin = Fout = 60%, the level stops changing.
  • 75. Unfortunately, at this new steady state condition, the measurement is at a new value below the set point. The error (r-c) is called offset. It is a steady state error and is characteristic of all proportional controllers. The magnitude of the offset depends on the size of the load change and the capacity (size) of the tank.
  • 78. The output of the proportional controller is proportional to the input. m = Ge When the controller is switched to automatic its output goes to zero since the error is zero. m = G (r-c) = 0 As the output goes to zero the valve shuts, decreasing the Fin to 0% and causing the level to decrease. The level will stop decreasing only when the supply balances the load. This balance will occur only if Fin becomes 50% again. If the process dictates that the gain of the controller should be 20 when controlling at 50% load. The controller will operate with a 2.5% error. 50 = 20 (2.5)
  • 79. 1. Proportional controllers always operate with an error. 2. The higher the controller gain, as dictated by the process gain, the smaller the error. (It should be pointed that the controller gain can not be set arbitrarily. It is dictated by the process gain and for a given loop gain has a reciprocal relationship to the controller gain).
  • 80. To accommodate zero error situations m = Ge + Bias The Bias term has a fixed value and does not have the ability to change. The Bias is the output of the controller whenever the error is zero. m = Bias , if e = 0 Apply this algorithm to the previous example. Assume that we put the controller in manual and adjust all the signals to 50%: r = c = Fin = Fout = 50%. When we place the controller in automatic: m = Ge + Bias m = 0 + Bias = Bias A typical Bias setting being 50%, m = 50%
  • 81. If the load changes an error will occur once again. m = Ge + Bias 60 = 20(e) + 50 20(e) = 10 e = 0.5% Some manufacturers write the expression m = (100/PB) e + Bias Proportional band is defined as the change in input required to produce a full range change in output due to proportional control action. It may also be seen as the change in measurement required to change the output 100% or to fully stroke the valve.
  • 83. Proportional Offset m = (100/PB)e + Bias Offset = e = (m - Bias)(PB/100) There are two conditions which can make the offset equal to zero or a very small value. 1) Small values of PB or high gains on the controller. Remember that the process dictates the controller gain or PB. It is not an arbitrarily assigned value. 2) If (m = bias): in this situation, when the load is equal to the Bias, there will be no offset. Since the Bias is fixed this implies that the load is also fixed.
  • 86. Application of Proportional-Only Control Proportional-only control is not a common control application. 1) Processes where precise control at the set point is not required. Processes where offset can be tolerated. 2) Processes where the load changes are infrequent (seasonal). This allows matching load with Bias to eliminate or minimize the offset. 3) Low gain processes. Typically these are large capacity processes with low process gains. The low gain of the process allows a high gain on the controller minimizing the offset.
  • 87. Advantages and Limitations of Proportional-Only Control Advantages Limitations Immediate response Offset Easy to tune Good period of response Simple
  • 88. Integral Algorithm The error in proportional algorithm could be eliminated if the two terms in the parenthesis were made to equal each other. Offset = e = (m - Bias) PB/100 Since the output of the controller m is directly related to the load our only choice is to vary the Bias term by making the Bias = m and thus eliminating the error. The integral mode fulfills this requirement by providing the variable Bias capability that automatically achieves this load balancing task while eliminating errors at steady state.
  • 89. mI=(1/I) edt + mo mI = Ti edt + mo where I = min./rep Ti = rep./min. mI : is the output of the integral-only controller. I : is the gain adjustment for the integral-only controller known as the integral or reset time. mo : is the controller output at the time integration starts
  • 92. Application of Integral-Only Control Whenever the integral mode is required in an application it is customary to have a small amount of proportional along with it. The integral mode eliminates the offset at a cost of slower loop response. Integral can be justified and should be the major contributor for the following applications. 1. Slow loops designed to produce slow corrective action. 2. The integral mode is the major contributor in fast flow control applications usually with a minor contribution from the proportional controller.
  • 93. Windup Saturation of the integral mode of a controller developing during times when control cannot be achieved, which causes the controlled variable to overshoot its setpoint when the obstacle to control is removed.
  • 94. Advantages and Limitations of Integral-Only Control Advantages Limitations Eliminates offset Slows the response Easy to tune Potential windup or saturation Reduces integrated error Unstable with NSR capacity. (Always oscillates with NSR)
  • 95. Proportional Plus Integral Algorithm The need for precise control with zero error at steady state brought the integral mode in the picture. The integral mode eliminated the error at steady state but at an unacceptable cost of a slow loop response. Combining the two modes in a PI controller is a very effective compromise suitable for most process applications.
  • 96. The following observations should be made: 1) Integral mode is a must for precise control. 2) The cost of integration is a slower response. 3) If unable to eliminate the error at steady state the potential exists for loss of control through what is known as windup or saturation.
  • 97. The PI is by far the most common algorithm used in process control applications. In most plants the PI controller is used in excess of 80% of the time. The reason for its popularity is due to the fact that the algorithm benefits by getting an instantaneous response due to error from the proportional mode and the elimination of steady state error from the integral mode.
  • 98. m = (100/PB) [e + (1/I) edt]
  • 99. Open Loop Response of PI Controllers
  • 100. Closed Loop Response of PI Controllers
  • 101. Advantages and Limitations of PI Control Advantages Limitations No offset More difficult to tune Can minimize integrated Windup or saturation error potential Reasonably good period of response
  • 102. Derivative Algorithm • In some applications the increased period of response due to the integral mode is not acceptable • Especially if we recognize that after an upset it takes about 3 cycles for a loop to settle down and reach steady state. • Furthermore in approximately 10% of the processes the natural period of the loop is rather long and the penalty of even longer periods due to the need of having integral is not desirable.
  • 103. •The natural period of a distillation column is typically several hours. •If a given column has a natural period of 4 hours and, assuming a penalty of a 50% longer period due to the integral mode. •It would take approximately 18 hours (4 x 3 x 1.5 = 18) for this loop to reach steady state. •The problem gets further aggravated if other upset(s) occurs before steady state is reached.
  • 105. Open Loop Response (D Setting Fixed)
  • 106. Proportional plus Derivative Algorithm •Remember that derivative-only controllers do not exist. •The derivative mode must be combined with a proportional or a proportional plus integral controller and the phase will be limited to some value less than +90%.
  • 107. The older version with the Derivative on error m = 100/PB ( e + Dde/dt ) + Bias
  • 108. The newer version with the Derivative on measurement m = 100/PB ( e - Ddc/dt ) + Bias
  • 109. Application of Proportional plus Derivative Controllers The proportional plus derivative controller is not a frequent choice in process control applications. Its major limitation is its inability to eliminate offset or steady state error. To apply the derivative mode we have to make sure that the controlled variable is free of noise.
  • 110. Regarding offset it has the same problem as the proportional-only controller. The addition of derivative however produces an improvement in the speed of response. PD controllers are recommended for large capacity processes where precise (set point) control is not required. The major application of this controller is in batch processes where because of the nature of the process (integrating process) it may not be desirable to use the integral mode.
  • 111. Advantages and Limitations of PD Controllers Advantages Limitations Good response period Offset Fastest to reach steady Can not handle noise state Easier to tune than PID Insufficient benefit on fast processes
  • 112. PID Algorithm This three-mode controller has the attributes of all the modes along with their limitations. In summary the PID uses the immediate response of the proportional mode followed by the integral mode's ability to eliminate the offset. The slowing down of the response due to integration is compensated for by the derivative mode.
  • 113. To justify the application of the PID controller the process should satisfy the following conditions: 1. The controlled variable should be free of noise. 2. The process should have a large capacity for optimum benefit. 3. The slower response due to the integral mode is not acceptable for good control.
  • 114. Summary of Closed Loop Responses
  • 115. Advantages and Limitations of PID Controllers Advantages Limitations Good period of response Noisy measurement Compensates for the slow Difficult to tune integral Minimizes integrated Windup concerns errors Optimizes control loops
  • 116. Procedure for Determining Process Characteristics 1. Let the system stabilize. 2. Open the loop by placing the controller in manual. 3. Make sure the system is at steady state, the output and the controlled variable maintaining their values. 4. Introduce a small disturbance by stepping up the output of the controller. 5. Record the reaction of the controlled variable. 6. Bring the output back to the normal operating point and switch to auto.
  • 120. Steady State Gains of Elements Steady state gain is simply the slope of the input- output relationship of the element's response curve when both the input and output are time invariant (do not vary with time).
  • 122. Linearization For Constant Loop Gain Instead of tuning at the highest gain condition to be on the safe side, a better solution to the non-linearity problem is to use a complementary linearizing element in the loop through either the valve or other element. The objective of good control is to make the loop gain independent of the operating point as much as possible.
  • 124. THE STEADY STATE GAIN OF MEASURING ELEMENTS/TRANSMITTERS
  • 125. Flow Transmitters The most common industrial flow applications involve one of the following measuring Devices. LINEAR DEVICES NON LINEAR DEVICES Magnetic Flow Meters Orifice Positive Displacement Meters Venturi Vortex Meters Flow Nozzle Turbine Meters Elbow Meters Ultrasonic Target Meters Rotameter Weirs Coriolis Flumes
  • 127. Linearizing With A Compensating Response It is possible to linearize the differential producer (orifice plate) with a complementary response curve. To find a curve (b) type function from one of the other elements in the loop, i.e. the valve. The advantage of this approach is the elimination of the need for a square root extractor. The disadvantage is that the loop will be operating with (Flow)2 information.
  • 128. Linearizing the Valve Characteristic
  • 130. Non-Linear Controllers As electronic controllers were introduced, it was possible to build non-linear PID controllers. In some applications it is not desirable to have a constant gain controller. Non-linear controllers were designed to handle processes with variable gain. They were set up to have low gain in the high-gain region of the process and high gain in the low-gain region of the process.
  • 131. Linearizing Process Characteristic with a Non-Linear Controller
  • 133. Linearizing a Non-Linear Process - Non- Uniform Tank
  • 135. Linearizing Processes Whose Gain Varies Inversely With Load
  • 137. Acceptable Tuning Criteria Used in the Process Industry
  • 138. • If safety is the primary concern, speed and efficiency can be sacrificed and a critically damped response might be the best choice. • If the objective is to eliminate the error and achieve steady state as quickly as possible after an upset, then some form of underdamped response will be the choice. Generally most of the better tuning techniques lead to an underdamped response, with some decay ratio and a specific speed of response (period.)
  • 139. Tuning Criteria Using Error Minimization Approaches The objective of a well-tuned loop is to eliminate the error as quickly as possible by bringing the measurement equal to the set point.
  • 140. Quarter Amplitude Decay Criteria (QAD) is one of the most common under-damped response criteria. The controller gain is adjusted so that the amplitude of each successive cycle is one quarter of the previous amplitude. Unfortunately, this criteria does not completely define the response. Beyond an amplitude decay ratio, it gives no other information as to what the optimum period of the response should be.
  • 141. There is no mathematical justification for the QAD response. Its popularity and acceptance are due to its open loop gain, which between 0.5 and 0.6 seems to be a reasonable compromise in damping and period.
  • 142. The main criticism of QAD as a criterion is that it gives no information about speed of response, or period of a loop, and as such, it does not indicate an optimum response. In two or three mode controllers such as PI or PID there are an infinite number of settings that will give you a QAD response, only one of which will have the correct period for optimum response.
  • 143. Tuning Criteria Using Integral Error Minimization These techniques are especially useful if energy is used to make the product. Minimization of the area (error) under the curve leads to less energy consumption and higher efficiency. There are various error minimization criteria, each having certain advantages and limitations, and different PID settings.
  • 144. Integrated Error (IE) IE = e dt Integral Absolute Error (IAE) IAE = e dt Integrated Squared Error (ISE) ISE = e2 dt Integrated Time Absolute Error (ITAE) ITAE = e t dt
  • 145. Robustness •A loop tuned to particular criteria raises the question of loop stability when process conditions change. • A robust control loop, has a safety factor built in to the controller tuning settings, allowing the loop to maintain stability even if the process undergoes moderate changes in gain or dead time.
  • 146. • A robustness plot allows an analysis of how safely a loop is tuned. The gain ratio is the ratio of the current process gain to the original process steady-state gain. The delay ratio is the ratio of the process dead time to the dead time existing when the process was tuned.
  • 147. Making PID Adjustments and Observing their Effect on Loop Response
  • 148. Proportional Band or Gain Adjustment
  • 149. To change the response of the loop, adjust only with: PB or Gain. Decrease the loop gain to less than one in order to dampen the response. The obvious choices of response for this controller would range from an overdamped response to a Quarter Amplitude Decay response (QAD). To get a QAD response the Proportional Band would have to be doubled (2 x PBu) to drive the loop gain to 0.5.
  • 151. The proportional band or gain adjustment can be summarized as follows: • Changing gain or PB affects only the damping of the response. • Increasing the PB setting decreases gain while the period stays roughly the same.
  • 152. Any change of period length over n is of minor consequence. The amount depending on the process characteristics. •For dead-time only processes there would be no period change at all. •For dead-time plus capacity processes the period might increase by 10 - 15% over the natural period n. It is best to consider the proportional adjustment as a gain adjustment with no significant effect on the period of response.
  • 155. PID Adjustment Suppose we find our damping to be acceptable, but the period of response, o is too long. We need to maintain our loop gain constant, but to either increase derivative action or decrease integral action. Changing either one alone will not only change o, but will also change the gain vector which will in turn affect loop gain.
  • 156. The correct procedure in this case would be to increase derivative gain GD, by increasing derivative time D, while at the same time to decrease integral gain GI by increasing integral time I. This will tend to increase derivative action while maintaining the length of the PID vector constant. As a result, damping will remain unchanged while response period o is decreased.
  • 157. Interacting And Noninteracting PID There are at least two ways in which three-mode PID controllers can be built. The PID algorithm discussed so far is an ideal noninteracting controller algorithm. The noninteracting controller is designed such that its derivative and integral modes are in a parallel path and act independently of each other. The interacting PID controller is designed such that the integral and derivative modes interact.
  • 160. Effective PID values in terms of the actual settings
  • 161. Reasons for Tuning Methods Over the years many tuning methods or approaches have been developed and used with varying degrees of success. There is no general agreement as to what method is the best to use, the preferred choice usually being the one, that the individual has the most experience with.
  • 162. • Some of the methods are trial and error solutions to finding the desired response; others rely on mathematical relationships. • The preferred tuning method might be, it is desirable to have the capability to apply more than one approach. • In some cases, process or operational constraints dictate the method to use. • With experience, you develop a feel of what approach works best for a given application, and tune accordingly.
  • 163. Keep in mind that any tuning method, will give you only preliminary settings, which require fine tuning later for optimum response. The various tuning methods can be grouped into closed- loop and open-loop categories.
  • 164. The main distinction between the two is as follows: •In the closed-loop methods, adjustments are made and tested with the controller in automatic. •In the open-loop methods, preliminary settings are calculated by an open loop test, with the controller in manual. These preliminary adjustments are introduced in the controller and tuning is continued with the controller in automatic.
  • 165. Summary of making PID adjustments and observing their effect on loop response The table is designed to assist the user in deciding which direction the adjustments should be made.
  • 166. Procedure for Trial and Error Constant Cycling Method P-Only Controller 1. Place controller in manual. 2. Increase proportional band to a safe wide value 3. Place controller in automatic. 4. Make a 5 - 10% set point change around the operating point. 5. Reduce PB until constant amplitude cycling occurs. 6. Double PB for QAD. Controller is tuned. 7. Make a small upset and observe the response. Measurement will not be at set-point at steady state.
  • 167. P + I Controller 1. Increase I-time to maximum min/rep or minimum rep/min. (This eliminates the integral action.) 2. Tune as a P-Only Controller. 3. Increase Integral gain until constant amplitude cycling occurs. 4. Double the I-time in min/rep for QAD. (Halve the I-time if in rep/min.) 5. Make upset and observe the response. Measurement should reach set-point at steady state.
  • 168. PID Controller (Interacting Types) 1. Adjust the integral time min/rep and proportional band to high values. 2. Adjust derivative time to a very low value. 3. Reduce PB until constant amplitude cycling just occurs. 4. Double PB for QAD. 5. Controller is now tuned as P-Only. 6. Increase derivative time until constant amplitude cycling occurs. 7. Cut derivative time by 1/2 for QAD. 8. Set integral time to a value of 2 to 4 times that of the derivative time. 9. Make upset and observe the response. Measurement should be at the set-point at steady state. 10. Readjust PB, I, and D small amounts to get desired response.
  • 169. Procedure for Ziegler-Nichols and Cohen-Coon Constant Amplitude Cycling Method 1. With the controller in manual, remove the Derivative and Integral modes. (Remove or turn off Derivative action. Set Integral to its lowest gain value, by setting to maximum min/rep or minimum rep/min.) Set the Proportional Band or gain to a safe value depending on the process. Examples of safe values of PB or Gain: · Flow PB 300-500 % or Gain 0.2 to 0.3 · Temperature PB 100 % or Gain 1.0 At this point, you have a low-gain, Proportional-only controller.
  • 170. 2. Switch the controller to automatic, put a small upset by introducing a 5-10% set-point change around the operating point and observing the response. You should get a safe sluggish response. 3. Increase the gain or decrease the Proportional Band and repeat step (2) until uniform or sustained oscillations occur as shown in curve (C). If the gain is too low such as curve (A) increase the gain or lower the PB. Avoid unstable responses such as curve (B). Record the following information at uniform oscillation. Make sure the oscillation is due to the loop gain and not due to a limit cycle. (e. g., Valve hitting the stops produces what looks like uniform oscillation but the gain > 1).
  • 173. Procedure for Obtaining a Process Reaction Curve and Optimum PID Settings from Ziegler-Nichols or Cohen-Coon Process Reaction Method
  • 174. 1. Let the system stabilize at the normal operating point (set point and load at normal.) 2. Open the loop by placing the controller in manual. The output should hold at the same value as in step (1). 3. Make sure the system is at steady state with the output and the controlled variable maintaining their values. 4. Introduce a small disturbance by stepping up the output of the controller. The resulting output change should have enough resolution for analysis. 5. Record the reaction of the controlled variable. This is where a fast speed recorder at the output of the transmitter (in the order 1 in./min) comes in handy. 6. Bring the output back to the normal operating point and switch controller back to auto.
  • 175. After obtaining the Process Reaction Curve, proceed to determine P, PI, or PID settings using either Ziegler-Nichols or Cohen and Coon equations as shown.
  • 177. Procedure and Summary of Integral Criteria- Driven Open-Loop Method Obtain a process reaction curve
  • 180. •If the load (Fw) suddenly increases, the temperature (T2) decreases. •The controller senses this and acts on this error through its algorithm. •In two to three cycles, the loop stabilizes.
  • 182. Cascade Control may be defined as, "control in which the output of one controller is the set point for another controller." The set point to the flow controller defines the amount of flow required. On an upset in flow, the controller repositions the valve to bring the flow to the set point, r.
  • 183. These cascade loops are known as the primary and secondary loops. The loop closest to the controlled variable is the primary loop and the loop manipulating the valve is the secondary loop. The primary loop is known also as the master loop, outer loop, or the slower loop. The secondary loop may be called the slave loop, the inner loop, or the faster loop.
  • 184. The purpose of cascading is to have the secondary loop compensate for any supply upsets that may occur before they can influence the primary controlled variable. A supply upset to the primary loop is in effect a load upset to the secondary loop, and a fast-acting secondary can immediately correct for it.
  • 188. Results and Considerations In order for the cascaded control scheme to function without adversely affecting the gain of the primary loop, The 1/ 2 ratio must exceed 4. The higher the ratio, the easier it is to cascade.
  • 189. Advantages of Cascade 1. Cascade control eliminates the effects of supply upsets. 2. Quicker return to set point in the primary loop and less integrated absolute error (IAE). 3. The secondary loop is more responsive to the demands of the primary. 4. The primary loop sets the amount of supply input rather than valve position. Thus, the effects of valve characteristics (including non-linearities) are minimized, and effectively removed.
  • 190. Limitations of Cascade 1. More expensive because of additional hardware needs. 2. The primary loop must be substantially slower than the secondary loop. 3. In some applications it is difficult to break the process into a primary and secondary loop and identify the supply variable. 4. Compared to a feedback loop, it is more difficult to start up and tune a cascade loop.
  • 191. Specific Cascade Applications Valve Positioner The primary reason for having a positioner is to remove hysteresis from the valve.
  • 192. Limit Cycling Limit cycling can be another consequence of hysteresis, or dead band. The limit cycle is a clipped sine wave of the manipulated variable. Controller adjustments (tuning) cannot eliminate these oscillations. Widening PB will increase the amplitude and the period of oscillation, while decreasing integral action reduces amplitude and increases the period. Recognizing a limit cycle wave (clipped sine wave) can eliminate some frustrating and unsuccessful tuning effort. The only solutions to a limit cycle are as follows: • Use a valve positioner or other cascade application. • Remove integral action from the controller.
  • 193. Temperature On Flow Cascade Control Temperature on flow is a good candidate for cascade control. The supply is well defined and the flow and temperature processes have significantly different natural periods allowing a good cascade within the natural period ratio criteria.
  • 194. Temperature-On-Temperature Cascade Control Of An Exothermic Reactor The idea here is to keep the temperature inside the reactor (T1) at the desired value by controlling the temperature of the jacket (T2) by manipulating cooling water flow to the jacket.
  • 195. Flow as the Inner Loop The secondary loop is frequently a flow loop as seen in the various temperature cascades. The benefits are that the flow loop protects the primary loop from supply upsets; overcomes non-linear valve characteristics; and, reduces the effect of valve friction on the primary controlled variable.
  • 196. Level on Flow (Valve Positioner) Cascade A level application requiring precise control and unable to attain it due to valve hysteresis or frequent supply upsets. It is a good candidate for level valve position cascade. A cascade through either a valve positioner or a flow loop can be used since the level loop (primary) is most likely four times slower than the valve position loop, so that the criteria 1/ 2 > 4 is not violated.
  • 197. Integral Windup Preventing Measures in Cascaded Loops If in attempting to eliminate a sustained error, the controller output goes beyond 0 to 100%, the controller is wound up. Windup occurs if the error persists, with the valve fully open and the controller output at 100%. The controller becomes saturated, with loss of control.
  • 199. Windup Prevention Measures Place controller in manual. The operator can intervene to get any controller (analog on digital) out of the windup state by putting it in manual. This is a simple solution, but not practical in most applications. Sooner or later this approach fails.
  • 201. 1. Place the primary controller in manual and the secondary controller to the local set point. 2. Tune the secondary controller as if it were the only control loop present. 3. Return the secondary controller to remote set point and place the primary controller in auto. 4. Now tune the primary loop as if it were the only control loop present. Remember, when tuning the primary controller that there should be no interaction between the primary and secondary loops.
  • 203. Feedback Loop Advantages • Does not require extensive knowledge of the process. • Easy to implement (start up and tune). • Requires minimal amount of hardware (least expensive control strategy.) • Can be successfully implemented most of the time. (Feedback is sufficient 80 -90 % of the time.) • Reasonably good control.
  • 204. Feedback Loop Disadvantages • Process characteristics dictate the response. • Response is oscillatory. • Cannot handle frequent load upsets. • Trial and error solution to valve position consumes more energy.
  • 205. If in addition to the load upsets the process was also subject to frequent supply upsets, cascade control was the solution.
  • 206. Feedforward or calculation control is the alternative control strategy when we are unwilling or unable to accept an oscillatory type of response in a given application, or if the load upsets are very frequent (< 3 n) the controlled variable does not have a chance to settle out.
  • 208. Feedforward Advantages • Can handle processes with frequent load upsets (< 3tn). • Potentially perfect control without oscillations. • Response virtually independent of process characteristics. • Minimum integrated errors (IE, IAE) can approach zero. • Avoiding a trial error search of valve position conserves energy.
  • 209. Feedforward Disadvantages • Requires more knowledge of the process. • Requires additional engineering effort and time. • Requires additional hardware for implementation. • More expensive than feedback control. • Economic justification to implement feedforward is made conditionally.
  • 210. Feedback Trim Loops The feedforward model attempts to predict the effect of steady state and dynamic loads on the product being made. It is not feasible to include all the loads that affect the product, in order to have a perfect feedforward model. It is impossible to come up with a perfect feedforward requiring the need to have a corrective feedback loop known as the feedback trim loop.
  • 212. Mass Flow Processes @ S.S. LEVEL = CONSTANT as dh/dt = 0 Thus the steady state calculation in this example will simply make the flow input equal to the flow output. @ S.S. Fin = Fout Therefore Fin = Fout
  • 214. Applying Feedback Trim Loop to Tank Level Application
  • 215. Single Element Drum Level Application
  • 216. •For negative feedback, an odd number of reverse-acting elements is needed. •The final actuator, process and transmitter are all direct-acting elements. •The controller is put in a reverse-acting mode for negative feedback.
  • 217. •In open-loop test to check, it is found that as the steam flow or load increases, the level in the drum initially increases (instead of decreasing as expected.) •Typically, the level will go up initially and then come down as shown, temporarily creating a positive feedback situation and loss of control. •This happens because as the load increases due to more steam flow, the pressure in the drum decreases, causing the liquid in the drum to temporarily increase or swell.
  • 219. Two-Element Feedforward Drum Level Application •During steady state operation the steam flow (load) information is used to control the feed water flow on a pound-to-pound basis responding immediately to any load changes. •The drum-level feedback trim loop provides the necessary slow corrections to bring measurement back to the set point. •This configuration assumes a linear and repeatable relationship between the load and the feed water valve. •If this is true then two-element control is sufficient.
  • 221. Three-Element Feedforward Drum Level Application
  • 222. Energy Flow Feedforward Applications • Energy flow processes vary in their complexity. • These processes must be sufficiently well defined before attempting feedforward control. • For a given process there may be several loads that affect the product from the steady state point of view.
  • 223. • Some of these load contributions are nonlinear and in some cases difficult to evaluate and implement in the model. • These are the type of processes that consist of multiple lags and long dead-times which make them difficult to control with a feedback loop and thus good candidates for a feedforward strategy.
  • 224. Simple Energy Flow Example •To implement this in a feedforward loop, measure Qout and put an equal amount of Qin. •If succeed, the temperature in the vessel will stay constant.
  • 225. Heat Exchanger Energy Flow Example
  • 226. Recognize that this equation is: 1. Steady state without any dynamic considerations. 2. Only the major loads are represented in the model. 3. Minor loads are not accounted for. These include: • losses to ambient, • measuring element and transmitter accuracy, • change in efficiency due to fouling (scaling) or change in operating point, • heat lost in condensate. 4. Supply variations relating to the energy of the steam (enthalpy) are not accounted for. This might dictate cascade for supply upsets, not uncommon in this type of application.
  • 229. Applying A Feedback Trim Loop To The Feedforward
  • 230. Trim Loop Characteristics: • Use a P + I controller tuned for a slow response, no QAD. • Typical settings require wide proportional bands (low gain) and relatively long integral times in min/rep (i.e. 2- 5 min/rep), no derivative action. • The idea is to take slow corrective action without affecting the major feedforward scheme. • Do not introduce non-linear elements that affect the gain versus operating point relationship of the loop.
  • 231. • Remember, if unable to linearize for constant loop gain, tune at the highest gain, sluggish response is acceptable in this case. • If the feedforward model is reasonably accurate, the trim controllers output should be 50% during normal operation. • If this is not the case, i.e., output of trim either high or low, there is a good chance that the model does not accurately represent all major loads.
  • 233. Ratio Control Scheme • Ratio is a rudimentary form of feedforward where one variable is controlled in ratio to another. • It is used in processes where two components are mixed together in a certain proportion or ratio. • The controlled variable in effect is the ratio.
  • 241. The typical applications of selector systems can be categorized as follows: • Protection against instrument failure • Control through most critical measurement • Protection of equipment (safety)
  • 242. Protection Against Instrument Failures Furnace Pressure Measurement Protection
  • 244. Control Through Most Critical Measurement
  • 245. Protection of Equipment (Safety) Parallel Metering Combustion Scheme In boiler applications the furnace control system must satisfy various needs: •Maintenance of safe furnace conditions •Maintenance of safe furnace pressure in balanced draft units •Satisfaction of the energy demand •Maintenance of correct air/fuel ratios
  • 247. Pumping Station On a Pipeline The system should provide protection against the following: • Cavitation. If the suction pressure drops below a predetermined low value, the valve starts closing to bring suction pressure up and avoid cavitation. • Motor Load. As the motor draws a current exceeding the motor specifications, the valve starts closing to protect the motor. • Downstream Pressure. If the discharge pressure attempts to exceed the maximum recommended downstream pressure, the valve closes to prevent overpressurizing process piping.
  • 249. Tuning Selective Loops • Tune each loop and testing the system for functionality. • When all loops are tuned, check scheme performance. • Control should alternate smoothly, without a "bump," automatically transferring from one controller to another through the selective system.
  • 251. •The word adapt means to change or fit by modification to new conditions. •An adaptive control system may be defined as a system whose parameters automatically change in response to changing process characteristics. •The automatic change of the control parameters allows compensation for the changes in the process characteristics and the maintenance of a constant loop gain. •A simple linearization to achieve constant steady state is not considered adaptation since all the controller functions remain the same.
  • 252. •A nonlinear controller typically used in a pH application operates at different gains based on the loop operating point. •This controller is not considered adaptive since its controller functions are fixed.
  • 253. •If the titration curve drifts (changes shape) the linearization loses its effectiveness and there is nothing the controller can do to take care of the problem. •Therefore, this is strictly nonlinear control. Remember, to be adaptive, the controller must change its parameters in order to accommodate the changing process parameters. •To accomplish this requires a more capable controller as well as additional communication between the process and the controller.
  • 254. Approaches to Adaptation A few approaches have been used to implement adaptive control strategies: • Gain scheduling or programmed adaptation - based on a change in a process variable i.e. the set point. • Feedforward adaptation - based on a change in load. • Feedback adaptation - based on a change in the controlled variable (measurement.)
  • 256. Example of Programmed Adaptation Using Process Variable Information
  • 262. Process Equations: C1 = K11g11m1 + K12g12m2 C2 = K21g21m1 + K22g22m2 Changing m1 affects both C1 and C2. Changing m2 affects both C2 and C1.
  • 264. Simultaneous Control of Pressure and Flow •This involves the simultaneous control of pressure and flow with the fact that both valves affect both the flow and the pressure. •The first consideration is to decide which valve should be assigned to control a particular variable. •The second consideration is whether a control system can be designed to cancel the interaction between two loops.
  • 266. AI - Analog Input The Analog Input block takes the input data from the Transducer block, selected by channel number, and makes it available to other function blocks at its output. 266
  • 267. DI - Discrete Input The DI block takes the manufacturer’s discrete input data, selected by channel number, and makes it available to other function blocks at its output. 267
  • 268. PUL – Pulse Input The Pulse Input Block provides analog values based on a pulse (counter) transducer input. There are two primary outputs available. An accumulation output is intended to be connected to an integrator block for differencing, conversion, and integration. This is most useful when the count rate is low relative to the block execution rate. For high count rates, the accumulated count of pulses per block execution can be interpreted as an analog rate (vs. accumulation) value and can be alarmed. 268
  • 269. PID - PID Control The PID block offers a lot of control algorithms that use the Proportional, integral and derivative terms. 269
  • 270. EPID – Enhanced PID Control The EPID block has all parameters of the PID block. Additionally it provides 4 types for bumpless transference from Manual mode to Auto mode, and also a special treatment for tracking outputs. APID – Advanced PID Control The advanced PID function block provides the following additional features comparing to the standard PID algorithm and the enhanced PID: • Selection of the terms (proportional, integral, derivative) calculated on error or process variable • PI Sampling algorithm • Adaptive gain • Configurable Limits of anti reset wind-up • Special treatment for the error • Discrete output to indicate the actual mode 270
  • 271. ARTH - Arithmetic The ARTH block can be used in calculating measurements from combinations of signals from sensors. It is not intended to be used in a control path, so it does not support cascades or back calculation. It does no conversions to percent, so scaling is not supported. It has no process alarms. 271
  • 272. SPLT-Splitter The Splitter block provides the capability to drive multiple outputs from a single input, usually a PID. This block would normally be used in split ranging or sequencing of multiple valve applications. Included in the block features are the capability to open valves as part of a predetermined schedule and leave open or closed a given valve after the controller has transitioned off the valve. The splitter supports two outputs. Since this block will participate in the control path after a PID block, back calculation support is included. 272
  • 273. CHAR - Signal Characterizer •The block calculates OUT_1 from IN_1 and OUT_2 from IN_2, according to a curve given by the points: [x1 ;y1 ], [x2 ; y2 ]..............[x21 ; y21] Where x corresponds to the Input and y to the Output. •OUT_1 is related to IN_1 and OUT_2 is related to IN_2 using the same curve, but there is no correlation between IN_1 and IN_2 or between OUT_1 and OUT_2. 273
  • 274. INTG – Integrator •The Integrator Function Block integrates a variable in function of the time or accumulates the counting of a Pulse Input block. The integrated value may go up, starting from zero, or down, starting from the trip value (parameter SP). The block has two inputs to calculate flow. •This block is normally used to totalize flow, giving total mass or volume over a certain time, or totalize power, giving the total energy. 274
  • 275. OSDL - Output Signal Selector and Dynamic Limiter The output signal selector and dynamic limiter block (OSDL) provides two different algorithms types. •As Output Selector the cascade input may be routed for one of two outputs based on the value of the OP_SELECT input parameter. •As Dynamic Limiter the cascade input is transferred to both output, but it is limited by the secondary inputs multiplied by a gain, plus a bias. The Dynamic LIMITER is extremely useful in one of its most important applications: combustion control with double cross limits. 275
  • 276. FMTH – Flexible Mathematical Block This block provides mathematical expression execution with inputs, outputs and auxiliary variables generated by the user, and also including conditional expressions. The FMTH block has the following characteristics: • It allows execute several mathematical expressions “customized” by user with input and output values, and also using auxiliary variables in these expressions. • Friendly edition of the mathematical expressions, similar to the Microsoft Excel. 276
  • 277. • It allows the usage of the following operations described in the table below: 277
  • 278. AO - Analog Output The Analog Output Block is a function block used by devices that work as output elements in a control loop, like valves, actuators, positioners, etc. The AO block receives a signal from another function block and passes its results to an output transducer block through an internal channel reference. 278
  • 279. DO - Discrete Output The DO block converts the value in SP_D to something useful for the hardware found at the CHANNEL selection. 279
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