Fuzzy Logic & Intelligent Control Systems ASSLAMU ALIKUM From Muhammad Khurram Shaikh BE (Elect) , NEDUET MC(CS) , Bradley Univ, Peoria, IL , USA mkshaikh@neduet.edu.pk

Fuzzy Logic Fuzzy logic emerged into the mainstream of information technology in the late 1980’s and early 1990’s. Fuzzy logic is an extension of classical Boolean logic. It implements logic on the continuous range of truth-values [0,1]. An extension of expert systems technology in which the rules can be expressed imprecisely.

Father of Fuzzy Logic Lotfi Asker Zadeh Born : February 12, 1921 Nationality : American Field Mathematics Institutions U.C Berkeley Alma mater Columbia University Known for Founder of Fuzzy Maths

Father of Fuzzy Logic Brief History Born in Baku , Azerbaijan as Lotfi Aliaskerzadeh (or Askar Zadeh), to a Russian mother and an Iranian father Grew up in Iran, studied at Alborz High School and Tehran University and moved to the USA in 1944. Received an S.M. degree in electrical engineering from MIT in 1946, and a PhD in electrical engineering from Columbia University in1949, where he taught for ten years, and was promoted to full professor in 1957. Taught at the UC Berkely since 1959.

Father of Fuzzy Logic Contd. Published his initial work on Fuzzy Set in 1965 in which he detailed the mathematics of fuzzy set theory. In 1973; he proposed his theory of fuzzy logic.

Introduction Since fuzzy logic can handle approximate information in a systematic way, it is ideal for controlling nonlinear systems and for modeling complex systems where an inexact model exists or systems where vagueness is common Fuzzy logic is designed for situations where information is inexact and traditional digital on/off decisions are not possible. It divides data into vague categories such as "hot", "medium" and "cold". Fuzzy Logic is the name of the debut album by the Super Furry Animals. The name comes from a mathematical term which describes terms that are easy to understand by humans but are not so easily understood by computers. For example 30C may be hot if it were the outside temperature but it would be cold if it were the temperature of a cup of tea. So whether it is hot or cold depends on the context.

Intro Contd. A conclusion reached by a computer recognizing that all values are not absolutes such as yes or no, black or white etc. Fuzzy logic makes calculations considering values in varying degrees between absolutes. For example, a computer might recognize black and white as absolutes, yet make an evaluation based on a shade of grey, which is somewhere between. A typical fuzzy system consists of fuzzy rule base, membership functions and an inference mechanism.

Applications Some of the major applications of fuzzy logic to expert system development include its use to: Control trains in Japan using fuzzy controllers (Miyamoto, Yasunobu) Cement kiln controller (Mamdani, Gaines) Z-II is a fuzzy ES shell used in medical diagnosis and risk analysis Video camera technology for automatic focusing, automatic exposure, image stabilization and white balancing Automobiles in cruise control, brake and fuel injection system Video and audio data compression Stock exchange activities (Yamaichi, Hitachi) Prevention of unwanted temperature fluctuations in air-conditioning systems (Sharp, Mitsubishi)

More Applications Examples where fuzzy logic is used Automobile and other vehicle subsystem Cameras Digital Image Processing e.g. Edge Detection Rice Cookers Dishwashers Elevators Washing Machines & other Home Appliances Video Game Artificial Intelligence Pattern Recognition in Remote Sensing Language Filters on message Boards and chat rooms Microcontrollers and microprocessors

FL Definitions Fuzzy set theory provides a formalism in which the conventional binary logic based on choices "yes" and "no" is replaced with a continuum of possibilities that effectively embody the alternative "maybe". Formally, the characteristic function of set X defined by f(x) =1 for all x in X and f(x)=0 for all x not in X is replaced by the membership function.

FL Definitions Contd. A form of logic in which variables can have degrees of truth or falsehood A system of logic dealing with the concept of partial truth with values ranging between “completely true” and “completely false.” It is often confused with probability, which represents the degree of possibility of an occurrence. Fuzzy logic sets need not sum to 1 as do probabilities. A form of artificial intelligence, stored on a computer chip, that enables a camcorder or television to make complex adjustments in focus or picture quality based on ideal models.

ALLAH HAFIZ SEE U SOON Muhammad Khurram Shaikh BE(Elect) NEDUET MS(CS) Bradley Peoria, IL, USA mkshaikh@neduet.edu.pk