# Fuzzy Logic based Questions and Answers

Q.1 Who is the founder of fuzzy logic?

Ans. Zader Lotfi is the founder of the fuzzy logic. He founded in the 60s the word ‘fuzzy’ itself.

Q.2 What is the reason that logic function has rapidly become one of the most successful technology for developing sophisticated control systems?

Ans. There are mainly two reasons:

(i)Fuzzy logic applies the concept of ‘certain degree’ which is similar to the way human beings think.Instead of just being either true or false,fuzzy logic can be true partially and also false partially at the same time.This is similar to the human mind.

(ii)Fuzzy logic can uses exact points representing to what degree an event occurs and with fuzzy rules it generates precise outcomes.

Q.3 What is sequence of steps taken in designing a fuzzy logic machine?

Ans. Following is the sequence for the designing a fuzzy logic machine:

Fuzzification->Rule Evaluation->Defuzzification

when designing a fuzzy logic,we first have to define the fuzzy sets and make appropriate member function.The rule evaluation comes in which matches the sets to its corresponding rules.

Q.4 What is the main difference between the probability and fuzzy logic?

Ans. Probability is ADDITIVE, means all its values must add up to one. This is main difference between fuzzy logic and probability. Although both probability and fuzzy logic contain values between the range of 1 and 0, fuzzy logic tells the extent of a specific member function, whereas probability gives the frequency,hence all values of its set must add up to

one.

Q.5 What is the fuzzy approximation theorem (FAT)?

Ans.The fuzzy approximation(FAT) as stated by Bart Kosko shows a fuzzy system, can model any continuous system. Each of the rules acts as a fuzzy patch that the system places so as to resemble the response of the continues system.

Q.6 What is an adaptive fuzzy system?

Ans. An Adaptive fuzzy machine works using the DIRO (Data in Rules Out) principle. This means that as data is fed into a black box, rules are generated. The black box is nueral network. Nueral networks are used to generate the fuzzy rules.

Q.7 What is the principle of fuzzy logic?

Ans. Fuzzy logic is a concept of ‘certain degree’. Japan is currently the most active users of fuzzy logic. Boolean logic is a subset of fuzzy logic*.*

Q.8 What is the artificial intelligence fuzzy logic?

Ans. Fuzzy logic is formed from many-logic values. It deals with reasoning that is approximate rather than fixed and exact. In contrast with traditional theory, where binary sets have two-valued logic: true or false, fuzzy logic variables may have a truth value that ranges in between 0 and 1.

Q.9 What are the types of fuzzy logic sets?

Ans. There are mainly two types of fuzzy sets:

(i) Type-1 fuzzy set

(ii) Type-2 fuzzy set

Q.10 What can we do with type-2 Fuzzy logic sets?

Ans. Whatever we do with type-1 fuzzy sets we can also do with type-2 fuzzy sets. Its how to do it that is different. For type-1 fuzzy sets, we perform set theoretic operations,such as union,intersection and complement. We can do the same for type-2 fuzzy sets. Procedures for how to do this have been worked out and are especially simple for interval type-2 fuzzy sets.

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Some of the Applications of fuzzy logic can be enumerated as follows

1. Application of fuzzy logic in commercial appliances specifically HVAC heating ventilation and cooling

2. Application in industrial automation

3. Application in signal processing of data

4. 3D animation system for generating crowd uses fuzzy logic system . This program was used extensively in the making of the Lord of the Rings trilogy as well as The Lion, The Witch and the Wardrobe films.

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FUZZY LOGIC is a problem-solving control system methodology that lends itself to implementation in systems ranging from simple, small, embedded micro-controllers to large, networked, multi-channel PC or workstation-based data acquisition and control systems. It can be implemented in hardware, software, or a combination of both. FL provides a simple way to arrive at a definite conclusion based upon vague, ambiguous, imprecise, noisy, or missing input information. FL’s approach to control problems mimics how a person would make decisions, only much faster. I would suggest interested people to read this article.

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