control of dc motor by using fuzzzy

1. SPEED CONTROL OF DC
MOTOR BY FUZZY
CONTROLLER
MD MUSTAFA KAMAL
ROLL NO 112509
M E (CONTROL AND INSTRUMENTATION)

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

28. 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

29. 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.

30. 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

31. 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.

32. THANK YOU