INTRODUCTION TO FUZZY LOGIC
Lecture 1
H.Metin Ertunç, PhD
2017, Fall
We use fuzzy logic technique for two
purposes
1. For making decision in any case
2. For control of industrial systems
Fuzzy logic:
●A way to represent variation or imprecision in
logic
●A way to make use of natural language in logic
●Approximate reasoning
Humans say things like "If it is sunny and warm
today, I will drive fast"
Linguistic variables:
＊ Temp: {freezing, cool, warm, hot}
＊ Cloud Cover: {overcast, partly cloudy, sunny}
＊ Speed: {slow, fast}
Definition
• Fuzzy logic is an approach to computing based on "degrees of truth"
rather than the usual "true or false" (1 or 0) Boolean logic on which the
modern computer is based.
• Fuzzy Logic is a form of many-valued logic in which the truth values of variables may be any real number between 0 and 1,
considered to be "fuzzy".
• By contrast, in Boolean Logic, the truth values of variables may only be the "crisp" values 0 or 1.
The difference between classic logic and
fuzzy logic
Fuzzy logic is a form of many-valued logic in which the truth values of variables may be any real number between 0 and 1, considered to be "fuzzy".
This is one in traditonal logic. What about this apple in
traditional logic? 0.7 apple in fuzzy logic
• The rule table must now be created to determine which output ranges are used.
• The table is an intersection of the two inputs.
• We have to figure out what to do with the result we get
from the rules and the fuzzy sets.
Advantages of fuzzy logic
• Conceptually easy to understand
• Flexible
• Tolerant to imprecise data
• Good for modeling of nonlinear functions
• Increased robustness.
• Simplify knowledge acquisition and representation.
• A few rules encompass great complexity.
Disadvantages of fuzzy logic
• Hard to develop a model from a fuzzy system
• Require more fine tuning and simulation
before operational
• Have a stigma associated with the word fuzzy
(at least in the Western world); engineers and
most other people are used to crispness and
shy away from fuzzy control and fuzzy decision
making
Application areas of fuzzy logic controllers
• Coal Power Plant
• Refuse Incineration Plant • Water Treatment Systems • AC Induction Motor
• Nuclear Fusion
• Truck Speed Limiter • Sonar Systems • Toasters • Photocopiers • Hi-Fi Systems • Humidifiers • Fraud Detection • Customer Targeting
• Creditworthiness Assessment
• Mortgage Application
• Domestic Goods - Washing
• Stock Prognosis
• Machines/Dryers
• Microwave Ovens
• Quality Control
• Speech Recognition
• Consumer Electronics – Television
• Still and Video Cameras - Auto
focus, Exposure and Anti-Shake
• Vacuum Cleaners
Applications..
• Automotive
Systems
Automatic
Gearboxes
Four-Wheel Steering
Vehicle environment
control
Applications..
• Consumer Electronic
Goods
Hi-Fi Systems
Photocopiers
Still and Video Cameras
Television
Applications
• Domestic Goods
Microwave Ovens
Refrigerators
Toasters
Vacuum Cleaners
Washing Machines
Applications
• Environment Control
Air
Conditioners/Dryers/Heaters
Humidifiers
Actual Implementations
And Application Areas
Of Fuzzy Logic
Nissan – fuzzy automatic transmission, fuzzy anti-skid braking
system
CSK, Hitachi – Hand-writing Recognition
Sony - Hand-printed character recognition
Ricoh, Hitachi – Voice recognition
NASA has studied fuzzy control for automated space docking:
simulations show that a fuzzy control system can greatly reduce
fuel consumption
Canon developed an auto-focusing camera that uses a
charge-coupled device (CCD) to measure the clarity of the image in six
regions of its field of view and use the information provided to
determine if the image is in focus. It also tracks the rate of change
of lens movement during focusing, and controls its speed to
Future expectations for fuzzy logic
In the future fuzzy logic will
be the most important issue
about technology for all
What is intelligence?
• The ability of a system to calculate, reason,
perceive relationships and analogies, learn from
experience, store and retrieve information from
memory, solve problems, comprehend complex
ideas, use natural language fluently, classify,
Intelligence and Brain
• There are over 100 billion neurons in the brain.
• They consist from a large body and long thin tail
• "axons“
• Electrical signals in neurons with axons of other cells is
transmitted to a speed of 100 meters per second.
• Neurons can sometimes transmit messages through a single
axon to the remote areas of the body. Some axons from the
brain to the spinal cord goes up, and their lengths can find
one meter.
Artificial Intelligence
• Artificial intelligence is the science and engineering
of making intelligent machines, especially intelligent
computer programs. It is related to the similar task
of using computers to understand human
intelligence, but AI does not have to confine itself to
methods that are biologically observable.
Artificial Intelligence and Fuzzy Logic
Artificial Intelligence (AI) can offer may advantages over
traditional methods, such as statistical analysis, particularly where the data exhibits some form of non-linearity. Some existing
application of spatial analysis and modeling techniques includes artificial neural networks and rule-based system fuzzy logic .
CONCLUSION
Fuzzy logic provides an alternative way to
represent linguistic and subjective attributes of
the real world in computing.
