Speed control of dc motor by fuzzy controller
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Speed control of dc motor by fuzzy controller

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    Speed control of dc motor by fuzzy controller Speed control of dc motor by fuzzy controller Presentation Transcript

    • SPEED CONTROL OF DC MOTORBY FUZZY CONTROLLER PREM KUMAR REG NO – 1611110018 M TECH (PED)
    • INTRODUCTION The fuzzy logic, unlike conventional logicsystem, is able to model inaccurate or imprecisemodels. The fuzzy logic approach offers a simpler,quicker and more reliable solution that is clearadvantages over conventional techniques. This paperdeals with speed control of Separately Excited DCMotor through fuzzy logic Controller.
    • WHAT IS FUZZY LOGIC CONTROLLERS ? It’s totally different from other controllers, fuzzy logics 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.
    • HOW DOES IT WORKS? In fuzzy logic we define human readable rulesto form the target system. For instance assume wewant to control the room temperature, first of all wedefine simple rules:  If the room is hot then cool it down  If the room is normal then dont change temperature  If the room is cold then heat it up
    • HOW DOES IT WORKS? CONT….
    • BOOLEAN LOGIC REPRESENTATION Slow Fast Speed = 0 Speed = 1 bool speed; get the speed if ( speed == 0) { // speed is slow } else { // speed is fast }
    • 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 ]
    • 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
    • FUZZY SET OPERATORS Union max (fA(x) , fB(x) ) Intersection min (fA(x) , fB(x) ) Complement Complement( fA(x) )
    • 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
    • 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.
    • STRUCTURE OF FUZZY LOGIC CONTROLLER ADC FUZZIFIER INFERENCE ENGINE DEFUZZIFIER DAC
    • FUZZIFICATION Conversion of real input to fuzzy set valuesPROCEDURE 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.
    • INFERENCE ENGINE Which makes the rules works in response to system inputs.
    • 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 ).
    • DEFUZZIFICATION Changing fuzzy output back into numericalvalues for system actionThere are two major defuzzification techniques1.Mean Of Maximum method (MOM)2.Gravity center defuzzifier (GCD)
    • DEFUZZIFICATION CONT…. Example let y = {0.1/2 + 0.8/3 + 1.0/4 + 0.8/5 +0.1/6} usingGCD method we haveY = ( 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
    • BLOCK DIAGRAM DC DC TO DC DC VOLTAGE CONVERTER MOTOR SOURCE PWM FUZZY GENERATOR CONTROLLER
    • 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
    • SYSTEM DESCRIPTION CONT…. A linear model of a simple DC motor consistsof a mechanical equation and electrical equation asdetermined in the following equations
    • SYSTEM DESCRIPTION CONT…. The dynamic model of the system is formedusing these differential equations
    • SYSTEM DESCRIPTION CONT…. DRIVER CIRCUIT : Here the DC to DC converter is used to controlthe armature voltage of the motor. The switches in the DC to DC converter arecontrolled by PWM inverter. The PWM which compares the correctederror(ce) signal generated by the fuzzy controller andreference signal.
    • SYSTEM DESCRIPTION CONT…. Dc source DC motor Speed Thyristor (armature) measurements PWM Fuzzy controller controllerRef signal
    • FUZZY LOGIC CONTROLLER In this controller the input is speed and theoutput is voltage.The membership function is figuredbetween error and change in error. After that usingpre defined rule the controller produces signal thissignal is called control variable.it is given to PWMcurrent controller
    • THE RULE DATABASE TABLE
    • ADVANTAGES OVER CONVENTIONAL CONTROLTECHNIQUES 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.
    • 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
    • CONCLUSION Thus the fuzzy logic controller is sensitive tovariation of the reference speed attention. It is alsoovercome the disadvantage of the use conventionalcontrol sensitiveness to inertia variation andsensitiveness to variation of the speed with drivesystem of dc motor.
    • THANK YOU