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

Slides:



Advertisements
Similar presentations
Fuzzy Logic 11/6/2001. Agenda General Definition Applications Formal Definitions Operations Rules Fuzzy Air Conditioner Controller Structure.
Advertisements


Automation I. Introduction. transmitter actuator Structure of control system Process or plant Material flow sensorstransducers actuating units actuating.

Fuzzy Logic and its Application to Web Caching
Fuzzy Expert System. Basic Notions 1.Fuzzy Sets 2.Fuzzy representation in computer 3.Linguistic variables and hedges 4.Operations of fuzzy sets 5.Fuzzy.
Fuzzy Expert Systems. Lecture Outline What is fuzzy thinking? What is fuzzy thinking? Fuzzy sets Fuzzy sets Linguistic variables and hedges Linguistic.
FUZZY SYSTEMS. Fuzzy Systems Fuzzy Sets – To quantify and reason about fuzzy or vague terms of natural language – Example: hot, cold temperature small,
Fuzzy Logic E. Fuzzy Inference Engine. “antecedent” “consequent”
FUZZY LOGIC Shane Warren Brittney Ballard. OVERVIEW What is Fuzzy Logic? Where did it begin? Fuzzy Logic vs. Neural Networks Fuzzy Logic in Control Systems.
Fuzzy Expert System.
11 Inverted Pendulum Emily Hamilton ECE Department, University of Minnesota Duluth December 21, 2009 ECE Fall 2009.
Fuzzy Medical Image Segmentation
Chapter 18 Fuzzy Reasoning.
1 Chapter 18 Fuzzy Reasoning. 2 Chapter 18 Contents (1) l Bivalent and Multivalent Logics l Linguistic Variables l Fuzzy Sets l Membership Functions l.
WELCOME TO THE WORLD OF FUZZY SYSTEMS. DEFINITION Fuzzy logic is a superset of conventional (Boolean) logic that has been extended to handle the concept.
Ming-Feng Yeh General Fuzzy Systems A fuzzy system is a static nonlinear mapping between its inputs and outputs (i.e., it is not a dynamic system).
Introduction What is Fuzzy Logic? HOW DOES FL WORK? Differences between Classical set (crisps) and Fuzzy set theory Example 1 Example 2 Classifying Houses.
Fuzzy Systems and Applications
The Equivalence between fuzzy logic controllers and PD controllers for single input systems Professor: Chi-Jo Wang Student: Nguyen Thi Hoai Nam Student.
Fuzzy Logic BY: ASHLEY REYNOLDS. Where Fuzzy Logic Falls in the Field of Mathematics  Mathematics  Mathematical Logic and Foundations  Fuzzy Logic.
Equivalence Class Testing
BEE4333 Intelligent Control
Fuzzy Logic. Priyaranga Koswatta Mundhenk and Itti, 2007.
GreenHouse Climate Controller Fuzzy Logic Programing Greenhouse Climate Controller Using Fuzzy Logic Programming Anantharaman Sriraman September 2, 2003.
FUZZY LOGIC Babu Appat. OVERVIEW What is Fuzzy Logic? Where did it begin? Fuzzy Logic vs. Neural Networks Fuzzy Logic in Control Systems Fuzzy Logic in.
Fuzzy logic Introduction 2 Fuzzy Sets & Fuzzy Rules Aleksandar Rakić
Fuzzy Logic Conception Introduced by Lotfi Zadeh in 1960s at Berkley Wanted to expand crisp logic.
Fuzzy Logic. WHAT IS FUZZY LOGIC? Definition of fuzzy Fuzzy – “not clear, distinct, or precise; blurred” Definition of fuzzy logic A form of knowledge.
بسم الله الرحمن الرحيم Islamic University of Gaza Electrical Engineering Department.
 Definition Definition  Bit of History Bit of History  Why Fuzzy Logic? Why Fuzzy Logic?  Applications Applications  Fuzzy Logic Operators Fuzzy.
FUZZY LOGIC 1.
Scope Richard Crowder. E 3 AN  Electrical  Electronic  Engineering.
Logical Systems and Knowledge Representation Fuzzy Logical Systems 1.
Fuzzy Systems Michael J. Watts
oPEN Simulation Environment PENSE PENSE PENSE is a simulation framework written in C++ using fully object oriented design patterns and it's designed.
Fuzzy Sets and Control. Fuzzy Logic The definition of Fuzzy logic is a form of multi-valued logic derived frommulti-valued logic fuzzy setfuzzy set theory.
“Principles of Soft Computing, 2 nd Edition” by S.N. Sivanandam & SN Deepa Copyright  2011 Wiley India Pvt. Ltd. All rights reserved. CHAPTER 12 FUZZY.
CSCI1600: Embedded and Real Time Software Lecture 12: Modeling V: Control Systems and Feedback Steven Reiss, Fall 2015.
Fuzzy systems. Calculate the degree of matching Fuzzy inference engine Defuzzification module Fuzzy rule base General scheme of a fuzzy system.
Homework 5 Min Max “Temperature is low” AND “Temperature is middle”
AI Fuzzy Systems. History, State of the Art, and Future Development Sde Seminal Paper “Fuzzy Logic” by Prof. Lotfi Zadeh, Faculty in Electrical.
Fuzzy Expert System n Introduction n Fuzzy sets n Linguistic variables and hedges n Operations of fuzzy sets n Fuzzy rules n Summary.
Could Be Significant.
Aisha Iqbal (CT-084) Kanwal Hakeem (CT-098) Tehreem Mushtaq (CT-078) Talha Syed (CT-111)
Fuzzy Logic 1. Introduction Form of multivalued logic Deals reasoning that is approximate rather than precise The fuzzy logic variables may have a membership.
Fuzzy Relations( 關係 ), Fuzzy Graphs( 圖 形 ), and Fuzzy Arithmetic( 運算 ) Chapter 4.
DDMAC: Dynamic Delayed Medium Access Control (MAC) Protocol with Fuzzy Technique for Wireless Body Area Network By: Ido Polak Netanel Ring.
CLOSED LOOP SPEED CONTROL OF DC MOTOR WITH PWM TECHNIQUE
Fuzzy Logic Workshop   Design of Fuzzy Controller for Temperature Chamber  
Introduction to Fuzzy Logic and Fuzzy Systems
Fuzzy Logic Control What is Fuzzy Logic ? Logic and Fuzzy Logic
Artificial Intelligence CIS 342
Fuzzy Systems Michael J. Watts
FUZZY NEURAL NETWORKS TECHNIQUES AND THEIR APPLICATIONS
Expert System Structure
A great man who created a complete new mathematics with many practical applications.
Fuzzy Logic 11/6/2001.
Building a Fuzzy Expert System
Artificial Intelligence
Stanisław H. Żak School of Electrical and Computer Engineering
Meaning of “fuzzy”, Definition of Fuzzy Logic
Fuzzy Logic and Fuzzy Sets
Homework 8 Min Max “Temperature is low” AND “Temperature is middle”
Dr. Unnikrishnan P.C. Professor, EEE
Fuzzy System Structure
FUZZIFICATION AND DEFUZZIFICATION
Homework 9 Min Max “Temperature is low” AND “Temperature is middle”
Fuzzy Logic Control EELE 6306
Fuzzy Logic KH Wong Fuzzy Logic v.9a.
Presentation transcript:

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

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.

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.

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

H OW DOES IT WORKS ? C ONT ….

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

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 ]

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

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) )

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

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.

S TRUCTURE OF FUZZY LOGIC CONTROLLER ADC FUZZIFIER INFERENCE ENGINE DEFUZZIFIER DAC

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.

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

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 ).

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)

D EFUZZIFICATION CONT …. Example let y = {0.1/ / / /5 +0.1/6} using GCD method we have Y = ( 0.1* * * *5 +0.1*6 ) ( ) Y=4

B LOCK DIAGRAM DC VOLTAGE SOURCE DC TO DC CONVERTER DC MOTOR FUZZY CONTROLLER PWM GENERATOR

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

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

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

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.

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

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

T HE RULE DATABASE TABLE

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

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.

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

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.

THANK YOU