Chapter Three
Other Control Configurations
Desired outcomes
upon completion of this topic, students should:
Understand different types of process control configurations
By Geremu G. 1
Feedback control system
Feedback Configuration: is a system whose output signal affects the controller through
feedback element (sensor/transducer).
Feedback control is an important technique that is widely used in the process industries.
Its main advantages are as follows.
Corrective action occurs as soon as the controlled variable deviates from the set point,
regardless of the source and type of disturbance.
Requires minimal knowledge about the process to be controlled. A mathematical
model of the process is not required, although it can be very useful for control system
design.
One type of feedback control system is PID controller which is both versatile and
robust. If process conditions change, retuning the controller usually produces
satisfactory control.
There are two types of feedback configurations
Positive feedback
Negative feedback
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Cont..
I. Positive feedback: The positive feedback adds the reference input, R(s) and feedback
output
Negative feedback: Negative feedback reduces the error between the reference input, R(s)
and system output.
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Effects of Feedback
Effect of feedback on overall gain: the negative feedback closed loop transfer function
is given by:
Depending on the value of (1+GH) the overall gain either decrease or increase
I. If 1 + 𝐺𝐻 > 1, over all gain decrease
II. If 1 + 𝐺𝐻 < 1, over all gain increase
Effect of feedback on sensitivity: sensitivity is the ratio of percentage change in closed
loop transfer function to the percentage change in open loop transfer function
Depending on the value of (1+GH) the sensitivity either decrease or increase
If (1+𝐺𝐻) > 1, sensitivity decrease
If (1+𝐺𝐻) < 1, sensitivity increase
2/12/2025 By Geremu G
Disadvantages of Feedback Control
Although feedback control is an important technique that is widely used in the process
industries, it has certain inherent disadvantages:
The following are some of the disadvantages:
No corrective action is taken until after a deviation in the controlled variable occurs.
Thus, perfect control, where the controlled variable does not deviate from the set
point during disturbance or set-point changes, is theoretically impossible.
Feedback control does not provide predictive control action to compensate for the
effects of known or measurable disturbances.
It may not be satisfactory for processes with large time constants and/or long time
delays. If large and frequent disturbances occur, the process may operate
continuously in a transient state and never attain the desired steady state.
In some situations, the controlled variable cannot be measured on-line, and,
consequently, feedback control is not feasible in such situation.
Therefore: in order to overcome these disadvantages other control techniques were
developed By Geremu G. 5
Feedforward Control
The basic concept of feedforward control is to measure important disturbance variables
and take corrective action before they upset (disturb) the process.
Basic requirements of feedforward control
The disturbance variables must be measured on-line.
To make effective use of feedforward control, at least a process model should be
available.
In particular, we need to know how the controlled variable responds to changes in
both the disturbance and manipulated variables.
The quality of feedforward control depends on the accuracy of the process model.
Ideal feedforward controllers that are theoretically capable of achieving perfect
control may not be physically realizable.
However, practical approximations of these ideal controllers often provide very
effective control.
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Structure of FB and FF controllers
Fig. (a) The feedback control of Fig. (b) The feedforward control of the
the liquid level in a boiler drum. liquid level in a boiler drum.
By Geremu G. 7
Cont.
A boiler drum with a conventional feedback control system is shown in Fig. (a). The level
of the boiling liquid is measured and used to adjust the feed-water flow rate.
This control system tends to be quite sensitive to rapid changes in the disturbance
variable, steam flow rate, as a result of the small liquid capacity of the boiler drum.
Rapid disturbance changes can occur as a result of downstream steam flow rate
On the other hand the feedforward control scheme in Fig. (b) can provide better control
of the liquid level. Here the steam flow rate is measured, and the feedforward controller
adjusts the feed-water flow rate.
In practical applications, feedforward control is normally used in combination with
feedback control.
Feedforward control is used to reduce the effects of measurable disturbances, while
feedback compensates for inaccuracies in the process model, measurement error, and
unmeasured disturbances.
These combination is therefore results in a precise control of dynamic processes.
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The structure of combined FB and FF control system
Fig. (c). The feedforward-feedback control of the boiler drum level.
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Ratio Control
Ratio control is a special type of feedforward control that has widespread application in
the process industries.
The objective is to maintain the ratio of two process variables as a specified value.
The two variables are usually flow rates, a manipulated variable ‘u’, and a disturbance
𝑢
variable ‘d’. Thus, the ratio 𝑅 = is controlled rather than the individual variables.
𝑑
Where ‘u’. and ‘d’. are physical variables, not deviation variables.
Typical applications of ratio control include:
Setting the relative amounts of components in blending operations
Maintaining a stoichiometric ratio of reactants to a reactor
Keeping a specified reflux ratio for a distillation column
Holding the fuel-air ratio to a furnace at the optimum value.
By Geremu G. 10
Structure of the two methods of ratio control system
Fig. (d). Ratio control, Method I
Fig. (e). Ratio control, Method II
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Cont.
Regardless of how ratio control is implemented, the process variables must be scaled
appropriately.
For example, in Method II the gain setting for the ratio station KR must take into account
the spans of the two flow transmitters.
𝑆𝑑
Thus, the correct gain for the ratio station is 𝐾𝑅 = 𝑅𝑑
𝑆𝑢
Where Rd is the desired ratio, Su and Sd are the spans of the flow transmitters for the
manipulated variable ‘u’ and disturbance variable ‘d’ streams, respectively.
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Cascade Control
In cascade control a process is controlled by two controllers in such a way that both are
acting for each other.
Cascade control is technique which contains two closed loop control cascade to each
other in such a way that first loop controller output will be set point for second loop
controller. It is called remote set point for second controller
In cascade control First Loop called Master Controller and second loop called Slave
Controller.
Master controller generate the set point for the slave controller.
Finally slave controller control the process depends upon the remote set point provide by
the master controller.
In simple closed loop control , controller is controlling single measured variable at a
point, so it is called single point closed loop control.
In short the process has only one stage information for control and less effective with
respect to change in set point that is why we need cascade control system.
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Block diagram of cascade control system
Terminologies are defined as:
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Advantage of cascade control
Reduce the dead time and phase lag time in the control system.
Can be combined with feed forward and other types of controllers.
Improved dynamic response and performance and provide limit on secondary variable.
In cascade we are controlling single variable in two stage. Therefore we have effective
control of process with respect to disturbance and set point change.
Cascade control are used where required precise and critical control.
Cascade control are able to compensate the load change of process and maintain at
desired set value of any physical quantity.
Cascade control should always be used if you have a process with relatively high
dynamics (likes level, temperature , composition, humidity ) and liquid or gas flow ,or
some other relatively-fast process, has to be manipulated to control the slow process.
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Draw backs of cascade control
Cascade control makes the system more complex.
Cascade control required more instruments and equipment which leads the cost of
process.
tuning of cascade controllers are more difficult than closed loop control.
It requires an additional measurement (usually flow rate) to work.
Cascade control should generally not be used if the inner loop is not at least three times
faster then the outer loop , because the improved performance may not justify the
added complexity.
By Geremu G. 16
Dead time control
Any delay in measurement, in controller action, in actuator operation, in computer
computation, and the like, is called transport delay or dead time.
It always reduces the stability of a system
Limits the achievable response time of the system.
Time delays or dead-time (DT) between inputs and outputs are very common in
industrial processes, engineering systems, economical, and biological systems.
Transportation and measurement lags, analysis times, computation and communication
lags all introduce DT into control loops.
DT is also used to compensate for model reduction where high-order systems are
represented by low-order models with delays.
In industries it can be known by two major consequences:
Complicates the analysis and design of feedback control systems
Makes satisfactory control more difficult to achieve
Therefore it is important to develop methods to mitigate the consequences of the dead
time (DT)
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Cont..
The most commonly used model to describe the dynamics of chemical processes is the
First-Order Plus Time Delay Model.
By proper choice of 𝜏𝐷𝑇 and τ, the model can be made to represent the dynamics of many
industrial processes.
Figure below shows the control structure of a First-Order Process with Dead Time
Fig. The control structure of a First-Order Process with Dead Time
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Cont..
The dead time in the above process can modeled as follow:
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Cont..
Dead-Time Approximations:
The simplest dead-time approximation can be obtained by taking the first two terms
of the Taylor series expansion of the transfer function of a dead-time element, 𝜏𝐷𝑇 .
The accuracy of this approximation depends on the dead time being sufficiently small
relative to the rate of change of the slope of qi(t). If qi(t) were a ramp (constant
slope), the approximation would be perfect for any value of 𝜏𝐷𝑇 . When the slope of
qi(t) varies rapidly, only small 𝜏𝐷𝑇 will give a good approximation.
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Cont..
Instability in feedback control systems results from an imbalance between system
dynamic lags and the strength of the corrective action.
When DT’s are present in the control loop, controller gains have to be reduced to
maintain stability
The larger the DT is relative to the time scale of the dynamics of the process, the larger
the reduction required and therefore results in poor performance and sluggish responses.
The time delay increases the phase shift proportional to frequency, with the
proportionality constant being equal to the time delay.
To avoid compromising performance of the closed-loop system, one must account for the
time delay explicitly,
e.g., Smith Predictor.
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Cont..
As shown in the above slide D(s) is a suitable compensator for a plant whose transfer
function, in the absence of time delay, is G(s).
With the compensator that uses the Smith Predictor, the closed-loop transfer function,
except for the factor 𝑒 −𝜏𝑠 , is the same as the transfer function of the closed-loop system
for the plant without the time delay and with the compensator D(s).
The time response of the closed-loop system with a compensator that uses a Smith
Predictor will thus have the same shape as the response of the closed-loop system without
the time delay compensated by D(s); the only difference is that the output will be delayed
by ‘τ’ seconds.
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