1. SPEED CONTROL OF DC MOTOR
BY FUZZY CONTROLLER
PREM KUMAR
REG NO – 1611110018
M TECH (PED)

2. INTRODUCTION
The fuzzy logic, unlike conventional logic
system, is able to model inaccurate or imprecise
models. The fuzzy logic approach offers a simpler,
quicker and more reliable solution that is clear
advantages over conventional techniques. This paper
deals with speed control of Separately Excited DC
Motor through fuzzy logic Controller.

3. WHAT IS FUZZY LOGIC CONTROLLERS ?
 It’s totally different from other controllers, fuzzy
logic's principle is to think like an organic creature;
human.
 A form of knowledge representation suitable for
notions that cannot be defined precisely, but which
depend upon their contexts.

4. HOW DOES IT WORKS?
In fuzzy logic we define human readable rules
to form the target system. For instance assume we
want to control the room temperature, first of all we
define simple rules:
 If the room is hot then cool it down
 If the room is normal then don't change
temperature
 If the room is cold then heat it up

5. HOW DOES IT WORKS? CONT….

6. BOOLEAN LOGIC REPRESENTATION
Slow Fast
Speed = 0 Speed = 1
bool speed;
get the speed
if ( speed == 0) {
// speed is slow
}
else {
// speed is fast
}

7. FUZZY LOGIC REPRESENTATION
Slowest
 For every problem
[ 0.0 – 0.25 ]
must represent in
terms of fuzzy sets.
Slow
[ 0.25 – 0.50 ]
Fast
[ 0.50 – 0.75 ]
Fastest
[ 0.75 – 1.00 ]

8. FUZZY SETS
 Extension of Classical Sets
 Fuzzy set is sets with smooth boundary
 Membership function
 A fuzzy set defined by the function that maps
objects in a domain of concern to their
membership value in the set. Such a function is
called membership function

9. FUZZY SET OPERATORS
 Union
max (fA(x) , fB(x) )
 Intersection
min (fA(x) , fB(x) )
 Complement
Complement( fA(x) )

10. LINGUISTIC VARIABLE
 Linguistic variables are the input (or) output variable
of the system. Whose values are in natural
language.
 Example:
The room is hot – linguistic value
How much it is hot – linguistic variable

11. TEMPERATURE CONTROLLER
 The problem
 Change the speed of a heater fan, based upon the room
temperature and humidity.
 A temperature control system has four settings
 Cold, Cool, Warm, and Hot
 Humidity can be defined by:
 Low, Medium, and High
 Using this we can define
the fuzzy set.

12. STRUCTURE OF FUZZY LOGIC CONTROLLER
ADC
FUZZIFIER
INFERENCE
ENGINE
DEFUZZIFIER
DAC

13. FUZZIFICATION
 Conversion of real input to fuzzy set values
PROCEDURE
 1. Description of the problem in an acceptable mathematical
form.
 2. Definition of the threshold for the variables, specifically the
two extremes of the greatest and least degree of satisfaction.
 Based on the above threshold values a proper membership
function is selected among those available e.g. linear, piece-
wise linear, trapezoidal, parabolic... etc.

14. INFERENCE ENGINE
 Which makes the rules works in response to
system inputs.

15. INFERENCE ENGINE CONT….
 These rules are human readable rules
 It is basically uses IF-THEN rules to manipulate
input variables.
 Example
IF( some function ) THEN( some function ).

16. DEFUZZIFICATION
Changing fuzzy output back into numerical
values for system action
There are two major defuzzification techniques
1.Mean Of Maximum method (MOM)
2.Gravity center defuzzifier (GCD)

17. DEFUZZIFICATION CONT….
 Example
let y = {0.1/2 + 0.8/3 + 1.0/4 + 0.8/5 +0.1/6} using
GCD method we have
Y = ( 0.1*2 + 0.8*3 + 1.0*4 + 0.8*5 +0.1*6 )
(0.1+ 0.8+ 1.0+ 0.8 +0.1)
Y=4

18. BLOCK DIAGRAM
DC
DC TO DC DC
VOLTAGE
CONVERTER MOTOR
SOURCE
PWM FUZZY
GENERATOR CONTROLLER

19. SYSTEM DESCRIPTION
 Motor model :
 In this model the armature reaction is neglected.
 The Vf and If are maintained constant. That is field
excited separately
 The armature voltage is controlled to get different
speed

20. SYSTEM DESCRIPTION CONT….
A linear model of a simple DC motor consists
of a mechanical equation and electrical equation as
determined in the following equations

21. SYSTEM DESCRIPTION CONT….
The dynamic model of the system is formed
using these differential equations

22. SYSTEM DESCRIPTION CONT….
 DRIVER CIRCUIT :
Here the DC to DC converter is used to control
the armature voltage of the motor.
The switches in the DC to DC converter are
controlled by PWM inverter.
The PWM which compares the corrected
error(ce) signal generated by the fuzzy controller and
reference signal.

23. SYSTEM DESCRIPTION CONT….
Dc source
DC motor Speed
Thyristor
(armature) measurements
PWM Fuzzy
controller controller
Ref signal

24. FUZZY LOGIC CONTROLLER
In this controller the input is speed and the
output is voltage.The membership function is figured
between error and change in error. After that using
pre defined rule the controller produces signal this
signal is called control variable.it is given to PWM
current controller

25. THE RULE DATABASE TABLE

26. ADVANTAGES OVER CONVENTIONAL CONTROL
TECHNIQUES
 Developing a fuzzy logic controller is cheaper than
developing model based or other controller with
comparable performance.
 Fuzzy logic controller are more robust than PID
controllers because they can cover a much wider
range of operating conditions.
 Fuzzy logic controller are customizable.

27. DISADVANTAGES OF FUZZY SYSTEM
 It is not useful for programs much larger or smaller
than the historical data.
 It requires a lot of data
 The estimators must be familiar with the historically
developed programs

28. CONCLUSION
Thus the fuzzy logic controller is sensitive to
variation of the reference speed attention. It is also
overcome the disadvantage of the use conventional
control sensitiveness to inertia variation and
sensitiveness to variation of the speed with drive
system of dc motor.

29. THANK YOU