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PID Controller
Lecture Outline
Introduction
• PID Stands for
– P  Proportional
– I  Integral
– D  Derivative
Introduction
• The usefulness of PID controls lies in their general
applicability to most control systems.
• In particular, when the mathematical model of the plant
is not known and therefore analytical design methods
cannot be used, PID controls prove to be most useful.
• In the field of process control systems, it is well known
that the basic and modified PID control schemes have
proved their usefulness in providing satisfactory control,
although in many given situations they may not provide
optimal control.
Introduction
• It is interesting to note that more than half of the
industrial controllers in use today are PID controllers or
modified PID controllers.
• Because most PID controllers are adjusted on-site, many
different types of tuning rules have been proposed in the
literature.
• Using these tuning rules, delicate and fine tuning of PID
controllers can be made on-site.
6
Four Modes of Controllers
• Each mode of control has specific advantages and
limitations.
• On-Off (Bang Bang) Control
• Proportional (P)
• Proportional plus Integral (PI)
• Proportional plus Derivative (PD)
• Proportional plus Integral plus Derivative (PID)
On-Off Control
• This is the simplest form of control.
Set point
Error
Output
8
Proportional Control (P)
• In proportional mode, there is a continuous linear relation
between value of the controlled variable and position of the
final control element.
• Output of proportional controller is
• The transfer function can be written as
-
𝑟(𝑡)
𝑏(𝑡)
𝑒(𝑡)
𝐾 𝑝
𝑐 𝑝(𝑡) = 𝐾𝑝 𝑒(𝑡)
𝑃𝑟𝑜𝑝𝑜𝑟𝑡𝑖𝑜𝑛𝑎𝑙
𝐶𝑜𝑛𝑡𝑟𝑜𝑙
𝑃𝑙𝑎𝑛𝑡
𝐹𝑒𝑒𝑑𝑏𝑎𝑐𝑘
𝑐(𝑡)
𝑐 𝑝(𝑡) = 𝐾𝑝 𝑒(𝑡)
𝐶 𝑝(𝑠)
𝐸(𝑠)
= 𝐾𝑝
9
Proportional Controllers (P)
• As the gain is increased the system responds faster to
changes in set-point but becomes progressively
underdamped and eventually unstable.
10
Proportional Plus Integral Controllers (PI)
• Integral control describes a controller in which the output
rate of change is dependent on the magnitude of the
input.
• Specifically, a smaller amplitude input causes a slower
rate of change of the output.
• Integral signal is sum of all instantaneous values, so when
integral and proportional terms are added the movement
get accelerated towards the set point.
11
Proportional Plus Integral Controllers (PI)
• The major advantage of integral controllers is that they have
the unique ability to return the controlled variable back to the
exact set point following a disturbance.
• Disadvantages of the integral control mode are that it
responds relatively slowly to an error signal and that it can
initially allow a large deviation at the instant the error is
produced.
• This can lead to system instability and cyclic operation. For
this reason, the integral control mode is not normally used
alone, but is combined with another control mode.
12
Proportional Plus Integral Control (PI)
𝑐 𝑝𝑖 𝑡 = 𝐾𝑝 𝑒 𝑡 + 𝐾𝑖 𝑒 𝑡 𝑑𝑡
-
𝑟(𝑡)
𝑏(𝑡)
𝑒(𝑡)
𝐾 𝑝
𝐾𝑖 𝑒(𝑡) 𝑑𝑡
𝑃𝑙𝑎𝑛𝑡
𝐹𝑒𝑒𝑑𝑏𝑎𝑐𝑘
𝑐(𝑡)
𝐾𝑖∫
+
+𝐾𝑝 𝑒(𝑡) 𝑐 𝑝𝑖 𝑡
13
Proportional Plus Integral Control (PI)
• The transfer function can be written as
𝐶 𝑝𝑖(𝑠)
𝐸(𝑠)
= 𝐾𝑝 + 𝐾𝑖
1
𝑠
𝑐 𝑝𝑖 𝑡 = 𝐾𝑝 𝑒 𝑡 + 𝐾𝑖 𝑒 𝑡 𝑑𝑡
14
Proportional Plus derivative Control (PD)
𝑐 𝑝𝑑 𝑡 = 𝐾𝑝 𝑒 𝑡 + 𝐾 𝑑
𝑑𝑒(𝑡)
𝑑𝑡
-
𝑟(𝑡)
𝑏(𝑡)
𝑒(𝑡)
𝐾𝑝
𝐾 𝑑
𝑑𝑒(𝑡)
𝑑𝑡
𝑃𝑙𝑎𝑛𝑡
𝐹𝑒𝑒𝑑𝑏𝑎𝑐𝑘
𝑐(𝑡)
𝐾 𝑑
𝑑
𝑑𝑡
+
+𝐾𝑝 𝑒(𝑡) 𝑐 𝑝𝑑 𝑡
15
Proportional Plus derivative Control (PD)
• The transfer function can be written as
𝐶 𝑝𝑑(𝑠)
𝐸(𝑠)
= 𝐾𝑝 + 𝐾 𝑑 𝑠
𝑐 𝑝𝑑 𝑡 = 𝐾𝑝 𝑒 𝑡 + 𝐾 𝑑
𝑑𝑒(𝑡)
𝑑𝑡
16
Proportional Plus derivative Control (PD)
• The stability and overshoot problems that arise when a
proportional controller is used at high gain can be reduced by
adding a term proportional to the time-derivative of the error signal.
The value of the damping can be adjusted to achieve a critically
damped response.
17
Proportional Plus derivative Control (PD)
• The higher the error signal rate of change, the sooner the final
control element is positioned to the desired value.
• 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 derivative (PD) control
because the derivative section responds to the rate of change of the
error signal.
• You can think of derivative control as a crude prediction of the error
in future, based on the current slope of the error. How far into the
future?
18
Proportional Plus Integral Plus Derivative Control (PID)
𝑐 𝑝𝑖𝑑 𝑡 = 𝐾𝑝 𝑒 𝑡 + 𝐾𝑖 𝑒(𝑡) 𝑑𝑡 + 𝐾 𝑑
𝑑𝑒(𝑡)
𝑑𝑡
-
𝑟(𝑡)
𝑏(𝑡)
𝑒(𝑡)
𝐾𝑝
𝐾 𝑑
𝑑𝑒(𝑡)
𝑑𝑡
𝑃𝑙𝑎𝑛𝑡
𝐹𝑒𝑒𝑑𝑏𝑎𝑐𝑘
𝑐(𝑡)
𝐾 𝑑
𝑑
𝑑𝑡
+
+𝐾𝑝 𝑒(𝑡) 𝑐 𝑝𝑖𝑑 𝑡
𝐾𝑖∫
𝐾𝑖 𝑒(𝑡) 𝑑𝑡
+
19
Proportional Plus Integral Plus Derivative Control (PID)
𝑐 𝑝𝑖𝑑 𝑡 = 𝐾𝑝 𝑒 𝑡 + 𝐾𝑖 𝑒(𝑡) 𝑑𝑡 + 𝐾 𝑑
𝑑𝑒(𝑡)
𝑑𝑡
𝐶 𝑝𝑖𝑑(𝑠)
𝐸(𝑠)
= 𝐾𝑝 + 𝐾𝑖
1
𝑠
+𝐾 𝑑 𝑠
Proportional Plus Integral Plus Derivative Control (PID)
• Although PD control deals neatly with the overshoot and ringing
problems associated with proportional control it does not cure the
problem with the steady-state error. Fortunately it is possible to
eliminate this while using relatively low gain by adding an integral
term to the control function which becomes
20
CL RESPONSE RISE TIME OVERSHOOT SETTLING TIME S-S ERROR
Kp Decrease Increase Small Change Decrease
Ki Decrease Increase Increase Eliminate
Kd
Small
Change
Decrease Decrease
Small
Change
The Characteristics of P, I, and D controllers
Tips for Designing a PID Controller
1. Obtain an open-loop response and determine what needs to be improved
2. Add a proportional control to improve the rise time
3. Add a derivative control to improve the overshoot
4. Add an integral control to eliminate the steady-state error
5. Adjust each of Kp, Ki, and Kd until you obtain a desired overall response.
• Lastly, please keep in mind that you do not need to implement all three
controllers (proportional, derivative, and integral) into a single system, if
not necessary. For example, if a PI controller gives a good enough response
(like the above example), then you don't need to implement derivative
controller to the system. Keep the controller as simple as possible.
The tuning parameters essentially determine:
1. How much correction should be made? The magnitude
of correction (change in control output) is determined by
the proportional mode of the controller.
2. How long the correction should be applied? The duration
of the adjustment to the controller output is determined
by the integral mode of the controller.
3. How fast should the correction be applied? The speed at
which the correction is made is determined by the
derivative mode of the controller.
PID TUNING RULES
Part-II
PID Tuning
• The transfer function of PID controller is given as
• It can be simplified as
• Where
𝐶 𝑝𝑖𝑑(𝑠)
𝐸(𝑠)
= 𝐾 𝑝 + 𝐾𝑖
1
𝑠
+𝐾𝑑 𝑠
𝐶 𝑝𝑖𝑑 𝑠
𝐸 𝑠
= 𝐾 𝑝(1 +
1
𝑇𝑖 𝑠
+𝑇𝑑 𝑠)
𝑇𝑖 =
𝐾𝑝
𝐾𝑖
𝑇𝑑 =
𝐾 𝑑
𝐾 𝑝
PID Tuning
• The process of selecting the controller parameters
(𝐾 𝑝, 𝑇𝑖 and 𝑇𝑑) to meet given performance specifications
is known as controller tuning.
• Ziegler and Nichols suggested rules for tuning PID
controllers experimentally.
• Which are useful when mathematical models of plants
are not known.
• These rules can, of course, be applied to the design of
systems with known mathematical models.
PID Tuning
• Such rules suggest a set of values of 𝐾𝑝, 𝑇𝑖 and 𝑇𝑑 that will
give a stable operation of the system.
• However, the resulting system may exhibit a large maximum
overshoot in the step response, which is unacceptable.
• In such a case we need series of fine tunings until an
acceptable result is obtained.
• In fact, the Ziegler–Nichols tuning rules give an educated
guess for the parameter values and provide a starting point
for fine tuning, rather than giving the final settings for
𝐾𝑝, 𝑇𝑖 and 𝑇𝑑 in a single shot.
Zeigler-Nichol’s PID Tuning Methods
• Ziegler and Nichols proposed rules for determining values
of the 𝐾 𝑝, 𝑇𝑖 and 𝑇𝑑 based on the transient response
characteristics of a given plant.
• Such determination of the parameters of PID controllers
or tuning of PID controllers can be made by engineers on-
site by experiments on the plant.
• There are two methods called Ziegler–Nichols tuning
rules:
• First method (open loop Method)
• Second method (Closed Loop Method)
Zeigler-Nichol’s First Method
• In the first method, we
obtain experimentally
the response of the
plant to a unit-step
input.
• If the plant involves
neither integrator(s) nor
dominant complex-
conjugate poles, then
such a unit-step
response curve may look
S-shaped
Zeigler-Nichol’s First Method
• This method applies if the response to a step input exhibits an
S-shaped curve.
• Such step-response curves may be generated experimentally
or from a dynamic simulation of the plant.
Table-1
Zeigler-Nichol’s Second Method
• In the second method, we first set 𝑇𝑖 = ∞ and 𝑇𝑑 = 0.
• Using the proportional control action only (as shown in
figure), increase Kp from 0 to a critical value Kcr at which
the output first exhibits sustained oscillations.
• If the output does not exhibit sustained oscillations for
whatever value Kp may take, then this method does not
apply.
Zeigler-Nichol’s Second Method
• Thus, the critical gain Kcr
and the corresponding
period Pcr are determined.
Table-2
Electronic PID Controller
𝑅1 𝑅2
𝑅 𝐷1
𝑅 𝐷2
𝐶 𝐷
𝐶𝐼
𝑅𝐼
𝑅3
𝑅4
𝑅5
𝑅6 𝑅7 𝑅8𝑒(𝑡)
𝐾𝑝 = −
𝑅2
𝑅1
𝑇𝑑 = −𝑅 𝐷2 𝐶 𝐷
𝑇𝑖 = −𝑅𝐼 𝐶𝐼
Electronic PID Controller
𝐸 𝑜(𝑠)
𝐸𝑖(𝑠)
=
𝑅4
𝑅3
(𝑅1 𝐶1 𝑠 + 1)(𝑅2 𝐶2 𝑠 + 1)
𝑅2 𝐶2 𝑠
𝐸 𝑜(𝑠)
𝐸𝑖(𝑠)
=
𝑅4 𝑅2
𝑅3 𝑅1
𝑅1 𝐶1 + 𝑅2 𝐶2
𝑅2 𝐶2
+
1
𝑅2 𝐶2 𝑠
+ 𝑅1 𝐶1 𝑠
Electronic PID Controller
𝐸 𝑜(𝑠)
𝐸𝑖(𝑠)
=
𝑅4 𝑅2
𝑅3 𝑅1
𝑅1 𝐶1 + 𝑅2 𝐶2
𝑅2 𝐶2
+
1
𝑅2 𝐶2 𝑠
+ 𝑅1 𝐶1 𝑠
𝐸 𝑜(𝑠)
𝐸𝑖(𝑠)
=
𝑅4 𝑅1 𝐶1 + 𝑅2 𝐶2
𝑅3 𝑅1 𝐶2
1 +
1
𝑅1 𝐶1 + 𝑅2 𝐶2 𝑠
+
𝑅1 𝐶1 𝑅2 𝐶2
𝑅1 𝐶1 +𝑅2 𝐶2
𝑠
𝐾𝑝 =
𝑅4 𝑅1 𝐶1 + 𝑅2 𝐶2
𝑅3 𝑅1 𝐶2
𝑇𝑖 = 𝑅1 𝐶1 + 𝑅2 𝐶2 𝑇𝑑 =
𝑅1 𝐶1 𝑅2 𝐶2
𝑅1 𝐶1 +𝑅2 𝐶2
• In terms of Kp, Ki, Kd we have
𝐾𝑝 =
𝑅4 𝑅1 𝐶1 + 𝑅2 𝐶2
𝑅3 𝑅1 𝐶2
𝐾𝑖 =
𝑅4
𝑅3 𝑅1 𝐶2
𝐾𝑑 =
𝑅4 𝑅2 𝐶1
𝑅3

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pid controller

  • 3. Introduction • PID Stands for – P  Proportional – I  Integral – D  Derivative
  • 4. Introduction • The usefulness of PID controls lies in their general applicability to most control systems. • In particular, when the mathematical model of the plant is not known and therefore analytical design methods cannot be used, PID controls prove to be most useful. • In the field of process control systems, it is well known that the basic and modified PID control schemes have proved their usefulness in providing satisfactory control, although in many given situations they may not provide optimal control.
  • 5. Introduction • It is interesting to note that more than half of the industrial controllers in use today are PID controllers or modified PID controllers. • Because most PID controllers are adjusted on-site, many different types of tuning rules have been proposed in the literature. • Using these tuning rules, delicate and fine tuning of PID controllers can be made on-site.
  • 6. 6 Four Modes of Controllers • Each mode of control has specific advantages and limitations. • On-Off (Bang Bang) Control • Proportional (P) • Proportional plus Integral (PI) • Proportional plus Derivative (PD) • Proportional plus Integral plus Derivative (PID)
  • 7. On-Off Control • This is the simplest form of control. Set point Error Output
  • 8. 8 Proportional Control (P) • In proportional mode, there is a continuous linear relation between value of the controlled variable and position of the final control element. • Output of proportional controller is • The transfer function can be written as - 𝑟(𝑡) 𝑏(𝑡) 𝑒(𝑡) 𝐾 𝑝 𝑐 𝑝(𝑡) = 𝐾𝑝 𝑒(𝑡) 𝑃𝑟𝑜𝑝𝑜𝑟𝑡𝑖𝑜𝑛𝑎𝑙 𝐶𝑜𝑛𝑡𝑟𝑜𝑙 𝑃𝑙𝑎𝑛𝑡 𝐹𝑒𝑒𝑑𝑏𝑎𝑐𝑘 𝑐(𝑡) 𝑐 𝑝(𝑡) = 𝐾𝑝 𝑒(𝑡) 𝐶 𝑝(𝑠) 𝐸(𝑠) = 𝐾𝑝
  • 9. 9 Proportional Controllers (P) • As the gain is increased the system responds faster to changes in set-point but becomes progressively underdamped and eventually unstable.
  • 10. 10 Proportional Plus Integral Controllers (PI) • Integral control describes a controller in which the output rate of change is dependent on the magnitude of the input. • Specifically, a smaller amplitude input causes a slower rate of change of the output. • Integral signal is sum of all instantaneous values, so when integral and proportional terms are added the movement get accelerated towards the set point.
  • 11. 11 Proportional Plus Integral Controllers (PI) • The major advantage of integral controllers is that they have the unique ability to return the controlled variable back to the exact set point following a disturbance. • Disadvantages of the integral control mode are that it responds relatively slowly to an error signal and that it can initially allow a large deviation at the instant the error is produced. • This can lead to system instability and cyclic operation. For this reason, the integral control mode is not normally used alone, but is combined with another control mode.
  • 12. 12 Proportional Plus Integral Control (PI) 𝑐 𝑝𝑖 𝑡 = 𝐾𝑝 𝑒 𝑡 + 𝐾𝑖 𝑒 𝑡 𝑑𝑡 - 𝑟(𝑡) 𝑏(𝑡) 𝑒(𝑡) 𝐾 𝑝 𝐾𝑖 𝑒(𝑡) 𝑑𝑡 𝑃𝑙𝑎𝑛𝑡 𝐹𝑒𝑒𝑑𝑏𝑎𝑐𝑘 𝑐(𝑡) 𝐾𝑖∫ + +𝐾𝑝 𝑒(𝑡) 𝑐 𝑝𝑖 𝑡
  • 13. 13 Proportional Plus Integral Control (PI) • The transfer function can be written as 𝐶 𝑝𝑖(𝑠) 𝐸(𝑠) = 𝐾𝑝 + 𝐾𝑖 1 𝑠 𝑐 𝑝𝑖 𝑡 = 𝐾𝑝 𝑒 𝑡 + 𝐾𝑖 𝑒 𝑡 𝑑𝑡
  • 14. 14 Proportional Plus derivative Control (PD) 𝑐 𝑝𝑑 𝑡 = 𝐾𝑝 𝑒 𝑡 + 𝐾 𝑑 𝑑𝑒(𝑡) 𝑑𝑡 - 𝑟(𝑡) 𝑏(𝑡) 𝑒(𝑡) 𝐾𝑝 𝐾 𝑑 𝑑𝑒(𝑡) 𝑑𝑡 𝑃𝑙𝑎𝑛𝑡 𝐹𝑒𝑒𝑑𝑏𝑎𝑐𝑘 𝑐(𝑡) 𝐾 𝑑 𝑑 𝑑𝑡 + +𝐾𝑝 𝑒(𝑡) 𝑐 𝑝𝑑 𝑡
  • 15. 15 Proportional Plus derivative Control (PD) • The transfer function can be written as 𝐶 𝑝𝑑(𝑠) 𝐸(𝑠) = 𝐾𝑝 + 𝐾 𝑑 𝑠 𝑐 𝑝𝑑 𝑡 = 𝐾𝑝 𝑒 𝑡 + 𝐾 𝑑 𝑑𝑒(𝑡) 𝑑𝑡
  • 16. 16 Proportional Plus derivative Control (PD) • The stability and overshoot problems that arise when a proportional controller is used at high gain can be reduced by adding a term proportional to the time-derivative of the error signal. The value of the damping can be adjusted to achieve a critically damped response.
  • 17. 17 Proportional Plus derivative Control (PD) • The higher the error signal rate of change, the sooner the final control element is positioned to the desired value. • 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 derivative (PD) control because the derivative section responds to the rate of change of the error signal. • You can think of derivative control as a crude prediction of the error in future, based on the current slope of the error. How far into the future?
  • 18. 18 Proportional Plus Integral Plus Derivative Control (PID) 𝑐 𝑝𝑖𝑑 𝑡 = 𝐾𝑝 𝑒 𝑡 + 𝐾𝑖 𝑒(𝑡) 𝑑𝑡 + 𝐾 𝑑 𝑑𝑒(𝑡) 𝑑𝑡 - 𝑟(𝑡) 𝑏(𝑡) 𝑒(𝑡) 𝐾𝑝 𝐾 𝑑 𝑑𝑒(𝑡) 𝑑𝑡 𝑃𝑙𝑎𝑛𝑡 𝐹𝑒𝑒𝑑𝑏𝑎𝑐𝑘 𝑐(𝑡) 𝐾 𝑑 𝑑 𝑑𝑡 + +𝐾𝑝 𝑒(𝑡) 𝑐 𝑝𝑖𝑑 𝑡 𝐾𝑖∫ 𝐾𝑖 𝑒(𝑡) 𝑑𝑡 +
  • 19. 19 Proportional Plus Integral Plus Derivative Control (PID) 𝑐 𝑝𝑖𝑑 𝑡 = 𝐾𝑝 𝑒 𝑡 + 𝐾𝑖 𝑒(𝑡) 𝑑𝑡 + 𝐾 𝑑 𝑑𝑒(𝑡) 𝑑𝑡 𝐶 𝑝𝑖𝑑(𝑠) 𝐸(𝑠) = 𝐾𝑝 + 𝐾𝑖 1 𝑠 +𝐾 𝑑 𝑠
  • 20. Proportional Plus Integral Plus Derivative Control (PID) • Although PD control deals neatly with the overshoot and ringing problems associated with proportional control it does not cure the problem with the steady-state error. Fortunately it is possible to eliminate this while using relatively low gain by adding an integral term to the control function which becomes 20
  • 21. CL RESPONSE RISE TIME OVERSHOOT SETTLING TIME S-S ERROR Kp Decrease Increase Small Change Decrease Ki Decrease Increase Increase Eliminate Kd Small Change Decrease Decrease Small Change The Characteristics of P, I, and D controllers
  • 22. Tips for Designing a PID Controller 1. Obtain an open-loop response and determine what needs to be improved 2. Add a proportional control to improve the rise time 3. Add a derivative control to improve the overshoot 4. Add an integral control to eliminate the steady-state error 5. Adjust each of Kp, Ki, and Kd until you obtain a desired overall response. • Lastly, please keep in mind that you do not need to implement all three controllers (proportional, derivative, and integral) into a single system, if not necessary. For example, if a PI controller gives a good enough response (like the above example), then you don't need to implement derivative controller to the system. Keep the controller as simple as possible.
  • 23. The tuning parameters essentially determine: 1. How much correction should be made? The magnitude of correction (change in control output) is determined by the proportional mode of the controller. 2. How long the correction should be applied? The duration of the adjustment to the controller output is determined by the integral mode of the controller. 3. How fast should the correction be applied? The speed at which the correction is made is determined by the derivative mode of the controller.
  • 25. PID Tuning • The transfer function of PID controller is given as • It can be simplified as • Where 𝐶 𝑝𝑖𝑑(𝑠) 𝐸(𝑠) = 𝐾 𝑝 + 𝐾𝑖 1 𝑠 +𝐾𝑑 𝑠 𝐶 𝑝𝑖𝑑 𝑠 𝐸 𝑠 = 𝐾 𝑝(1 + 1 𝑇𝑖 𝑠 +𝑇𝑑 𝑠) 𝑇𝑖 = 𝐾𝑝 𝐾𝑖 𝑇𝑑 = 𝐾 𝑑 𝐾 𝑝
  • 26. PID Tuning • The process of selecting the controller parameters (𝐾 𝑝, 𝑇𝑖 and 𝑇𝑑) to meet given performance specifications is known as controller tuning. • Ziegler and Nichols suggested rules for tuning PID controllers experimentally. • Which are useful when mathematical models of plants are not known. • These rules can, of course, be applied to the design of systems with known mathematical models.
  • 27. PID Tuning • Such rules suggest a set of values of 𝐾𝑝, 𝑇𝑖 and 𝑇𝑑 that will give a stable operation of the system. • However, the resulting system may exhibit a large maximum overshoot in the step response, which is unacceptable. • In such a case we need series of fine tunings until an acceptable result is obtained. • In fact, the Ziegler–Nichols tuning rules give an educated guess for the parameter values and provide a starting point for fine tuning, rather than giving the final settings for 𝐾𝑝, 𝑇𝑖 and 𝑇𝑑 in a single shot.
  • 28. Zeigler-Nichol’s PID Tuning Methods • Ziegler and Nichols proposed rules for determining values of the 𝐾 𝑝, 𝑇𝑖 and 𝑇𝑑 based on the transient response characteristics of a given plant. • Such determination of the parameters of PID controllers or tuning of PID controllers can be made by engineers on- site by experiments on the plant. • There are two methods called Ziegler–Nichols tuning rules: • First method (open loop Method) • Second method (Closed Loop Method)
  • 29. Zeigler-Nichol’s First Method • In the first method, we obtain experimentally the response of the plant to a unit-step input. • If the plant involves neither integrator(s) nor dominant complex- conjugate poles, then such a unit-step response curve may look S-shaped
  • 30. Zeigler-Nichol’s First Method • This method applies if the response to a step input exhibits an S-shaped curve. • Such step-response curves may be generated experimentally or from a dynamic simulation of the plant. Table-1
  • 31. Zeigler-Nichol’s Second Method • In the second method, we first set 𝑇𝑖 = ∞ and 𝑇𝑑 = 0. • Using the proportional control action only (as shown in figure), increase Kp from 0 to a critical value Kcr at which the output first exhibits sustained oscillations. • If the output does not exhibit sustained oscillations for whatever value Kp may take, then this method does not apply.
  • 32. Zeigler-Nichol’s Second Method • Thus, the critical gain Kcr and the corresponding period Pcr are determined. Table-2
  • 33. Electronic PID Controller 𝑅1 𝑅2 𝑅 𝐷1 𝑅 𝐷2 𝐶 𝐷 𝐶𝐼 𝑅𝐼 𝑅3 𝑅4 𝑅5 𝑅6 𝑅7 𝑅8𝑒(𝑡) 𝐾𝑝 = − 𝑅2 𝑅1 𝑇𝑑 = −𝑅 𝐷2 𝐶 𝐷 𝑇𝑖 = −𝑅𝐼 𝐶𝐼
  • 34. Electronic PID Controller 𝐸 𝑜(𝑠) 𝐸𝑖(𝑠) = 𝑅4 𝑅3 (𝑅1 𝐶1 𝑠 + 1)(𝑅2 𝐶2 𝑠 + 1) 𝑅2 𝐶2 𝑠 𝐸 𝑜(𝑠) 𝐸𝑖(𝑠) = 𝑅4 𝑅2 𝑅3 𝑅1 𝑅1 𝐶1 + 𝑅2 𝐶2 𝑅2 𝐶2 + 1 𝑅2 𝐶2 𝑠 + 𝑅1 𝐶1 𝑠
  • 35. Electronic PID Controller 𝐸 𝑜(𝑠) 𝐸𝑖(𝑠) = 𝑅4 𝑅2 𝑅3 𝑅1 𝑅1 𝐶1 + 𝑅2 𝐶2 𝑅2 𝐶2 + 1 𝑅2 𝐶2 𝑠 + 𝑅1 𝐶1 𝑠 𝐸 𝑜(𝑠) 𝐸𝑖(𝑠) = 𝑅4 𝑅1 𝐶1 + 𝑅2 𝐶2 𝑅3 𝑅1 𝐶2 1 + 1 𝑅1 𝐶1 + 𝑅2 𝐶2 𝑠 + 𝑅1 𝐶1 𝑅2 𝐶2 𝑅1 𝐶1 +𝑅2 𝐶2 𝑠 𝐾𝑝 = 𝑅4 𝑅1 𝐶1 + 𝑅2 𝐶2 𝑅3 𝑅1 𝐶2 𝑇𝑖 = 𝑅1 𝐶1 + 𝑅2 𝐶2 𝑇𝑑 = 𝑅1 𝐶1 𝑅2 𝐶2 𝑅1 𝐶1 +𝑅2 𝐶2 • In terms of Kp, Ki, Kd we have 𝐾𝑝 = 𝑅4 𝑅1 𝐶1 + 𝑅2 𝐶2 𝑅3 𝑅1 𝐶2 𝐾𝑖 = 𝑅4 𝑅3 𝑅1 𝐶2 𝐾𝑑 = 𝑅4 𝑅2 𝐶1 𝑅3