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

2. I NTRODUCTION 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. W HAT IS F UZZY 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. H OW 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. H OW DOES IT WORKS ? C ONT ….

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

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

8. F UZZY 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. F UZZY SET OPERATORS Union max (f A (x), f B (x) ) Intersection min (f A (x), f B (x) ) Complement Complement( f A (x) )

10. L INGUISTIC 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. S TRUCTURE OF FUZZY LOGIC CONTROLLER ADC FUZZIFIER INFERENCE ENGINE DEFUZZIFIER DAC

13. F UZZIFICATION 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. I NFERENCE E NGINE Which makes the rules works in response to system inputs.

15. I NFERENCE E NGINE 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. D EFUZZIFICATION 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. D EFUZZIFICATION 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. B LOCK DIAGRAM DC VOLTAGE SOURCE DC TO DC CONVERTER DC MOTOR FUZZY CONTROLLER PWM GENERATOR

19. S YSTEM DESCRIPTION Motor model :  In this model the armature reaction is neglected.  The V f and I f are maintained constant. That is field excited separately  The armature voltage is controlled to get different speed

20. S YSTEM 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. S YSTEM DESCRIPTION CONT …. The dynamic model of the system is formed using these differential equations

22. S YSTEM 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. S YSTEM DESCRIPTION CONT …. Thyristor DC motor (armature) DC motor (armature) Speed measurements Fuzzy controller PWM controller Dc source Ref signal

24. F UZZY 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. T HE RULE DATABASE TABLE

28. D ISADVANTAGES 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. A DVANTAGES 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. D ISADVANTAGES 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. C ONCLUSION 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