Cold Junction Compensation
FEEDBACK CONTROL SYSTEM
Engr Kashan Hussain
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A control system is a device, or set of devices, that manages, commands, directs or regulates the
behavior of other device(s) or system(s). Industrial control systems are used in industrial
production for controlling equipment or a machine.
For example, consider an elevator .When the fourth-floor button is pressed on the first floor, the
elevator rises to the fourth floor with a Speed and floor-leveling accuracy designed for passenger
comfort. The Push of the fourth-floor button is an input that represents our desired output.
Types of Control System:
Open-Loop Control Systems:
An open-loop controller, also called a non-feedback controller, is a type of controller that
computes its input into a system using only the current state and its model of the system.
Closed-Loop Control Systems:
Utilizes feedback to compare the actual output to the desired output response
Feedback Control system:
A system in which the values of some output quantities is controlled by feeding back the value of
the controlled quantity and using it to manipulating input quantity so as to bring the value of the
controlled quantity closer to the desired value is known as feedback control system.
In feedback control, the variable being controlled is measured and compared with a target value.
This difference between the actual and desired value is called the error. Feedback control
manipulates an input to the system to minimize this error. Figure shows an overview of a basic
feedback control loop. The error in the system would be the Output - Desired Output. Feedback
control reacts to the system and works to minimize this error. The desired output is generally
entered into the system through a user interface. The output of the system is measured (by a flow
meter, thermometer or similar instrument) and the difference iscalculated. This difference is used
to control the system inputs to reduce the error in the system.
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Feedback control can also be demonstrated with human behavior. For example, if a person goes
outside in Michigan winter, he or she will experience a temperature drop in the skin. The brain
(controller) receives this signal and generates a motor action to put on a jacket. This minimizes
the discrepancy between the skin temperature and the physiological set point in the person.
Types of feedback control system:
There are two types of feedback control systems
By definition, negative feedback is when a change (increase/decrease) in some variable results in
an opposite change (decrease/increase) in a second variable.Negative feedback is when the
output quantity or signal lowers the input quantity or signal. Negative feedback is used in natural
and artificial regulatory mechanisms, as well as in the design of oscillators.
As opposed to negative feedback, positive feedback is when a change (increase/decrease) in
some variable results in a subsequently similar change (increase/decrease) in a second variable.
In some cases, positive feedback leads to an undesirable behavior whereby the system diverges
away from equilibrium.
Proportional Integral (PI) control:
A PI controller is special case of PID controller in which the derivative (D) of the error is not
used.The controller output is given by
is the error or derivation of the actual measured value (PV) from the set point (SP)
= Proportional gain
PI controllers have two tuning parameters to adjust. While this makes them more challenging to
tune than a P-Only controller, they are not as complex as the three parameter PID controller.
Integral action enables PI controllers to eliminate offset, a major weakness of a P-only controller.
Thus, PI controllers provide a balance of complexity and capability that makes them by far the
most widely used algorithm in process control applications.
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Setting value of Kp is often a tradeoff between decreasing overshoot and increasing settling time.
The lack of derivative action makes the system steadier in the steady state in the case of noisy
data. This is because the derivative action is more sensitive to higher frequencies term in the
inputs. Without derivative action, a PI-controlled system is less responsive to real (non-noisy)
and relatively fast alternation in the state and so the system will be slower to reach set point and
slower to respond to perturbation than a well-tuned PID system may be.
Proportional derivative (PD) controller:
The added derivative action reduces initial overshoot of the measured variable, and therefore aids
in stabilizing the process sooner. This control mode is called proportional plus rate (PD) control
because the derivative section responds to the rate of change of the error signal.
The derivative function responds to the rate of change of proportional offset over time. As with
integral action, there are numerous ways to actually accomplish this. In the general case, the
derivative function looks at the rate at which the proportional offset changes over time (thus the
term derivative) and adjusts the output of the controller as required to minimize the rate of
change. When properly applied, the derivative function will help to minimize the deviation from
set point that a system will experience when it sees a sudden change in the requirements of the
process. The need for this function is not common in HVAC systems, and thus it is often not
necessary to implement it. However, the function can be useful to help minimize the swings that
a system will see at startup or due to some other large load change. Experience has shown it to be
particularly helpful in minimizing pressure deviations in large variable air volume systems at
start-up and in dealing with the problems associated with marginally oversized valves and other
final control elements.
One of the interesting aspects of derivative action is that it only will occur during an upset when
there is a change in offset relative to time. If the rate of changeof offset is zero, then the
derivative gain is multiplied by zero and will have no effect on the output.
Proportional Integral Derivative (PID) control:
A PID (Proportional Integral Derivative) controller is a common instrument used in industrial
control applications. A PID controller can be used for regulation of speed, temperature, flow,
pressure and other process variables. Field mounted PID controllers can be placed close to the
sensor or the control regulation device and be monitored centrally using a SCADA system.
The PID controller is a “three mode” controller. That is, its activity and performance is based on
the values chosen for three tuning parameters, one each nominally associated with the
proportional, integral and derivative terms. With the addition of a third adjustable tuning
parameter, the number of algorithm permutations increases markedly.
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PID controller calculates an “error” value as the difference between measured value and desired
set point. The controller attempts to minimize the error by adjusting the process control inputs.
Comparison between PI, PD and PID:
A proportional controller (Kp) will have the effect of reducing the rise time and will reduce but
never eliminate the steady-state error. An integral control (Ki) will have the effect of eliminating
the steady-state error for a constant or step input, but it may make the transient response slower.
A derivative control (Kd) will have the effect of increasing the stability of the system, reducing
the overshoot, and improving the transient response. The effects of each of controller parameters,
Kp, Kd, and ki on a closed-loop system are summarized in the table below.
Parameter Rise Time
If Kd Small,
Note that these correlations may not be exactly accurate, because, Kp, Kd, and ki, are dependent
on each other. In fact, changing one of these variables can change the effect of the other two. For
this reason, the table should only be used as a reference when you are determining the values for
Kp, Kd, and ki.
The PI-control lacks the D-control of the PID system. PI control is a form of feedback control. It
provides a faster response time than I-only control due to the addition of the proportional action.
PI control stops the system from fluctuating, and it is also able to return the system to its set
point. Although the response time for PI-control is faster than I-only control, it is still up to 50%
slower than P-only control. Therefore, in order to increase response time, PI control is often
combined with D-only control.
The PD-control lacks the I-control of the PID system. PD-control is combination of feed forward
and feedback control, because it operates on both the current process conditions and predicted
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process conditions. In PD-control, the control output is a linear combination of the error signal
and its derivative. PD-control contains the proportional control’s damping of the fluctuation and
the derivative control’s prediction of process error.
Proportional-integral-derivative control is a combination of all three types of control methods.
PID-control is most commonly used because it combines the advantages of each type of control.
This includes a quicker response time because of the P-only control, along with the
decreased/zero offset from the combined derivative and integral controllers. This offset was
removed by additionally using the I-control. The addition of D-control greatly increases the
controller's response when used in combination because it predicts disturbances to the system by
measuring the change in error. On the contrary, as mentioned previously, when used
individually, it has a slower response time compared to the quicker P-only control. However,
although the PID controller seems to be the most adequate controller, it is also the most
expensive controller. Therefore, it is not used unless the process requires the accuracy and
stability provided by the PID controller
Fuzzy logic controllers:
A fuzzy control system is a control system based on fuzzy logic—a mathematical system that
analyzes analog input values in terms of logical variables that take on continuous values between
0 and 1, in contrast to classical or digital logic, which operates on discrete values of either 1 or 0
(true or false, respectively).
The name implies that you have to be a bit fuzzy headed to use fuzzy logic!
Benefits Of Fuzzy logic Controllers:
Can be easily modified
Can use multiple inputs and outputs sources
Much simpler than its predecessors (linear algebraic equations)
Very quick and cheaper to implement
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