Advantages Of Fuzzy Logic

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In a narrow sense, fuzzy logic can be defined as a logical system, which is an expansion of multi-valued logic. Whereas in a wider sense it is almost similar with fuzzy sets theory. It is a method for computing based on "degrees of truth or fact" rather than the "true or false" (1 or 0). The idea of fuzzy logic was first proposed by Dr. Lotfi Zadeh of the University of California at Berkeley in the 1965 [62].
A fuzzy logic system (FLS) can be defined as the nonlinear mapping of an input data set to a scalar output data [63]. It works like a way that human brain works. The data are get together and form a number of partial facts or truths which are made aggregate further into higher level of truths. If these truths crosses certain level of
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Fuzzy logic is theoretically easy to understand: The concept has been used in fuzzy reasoning is quiet easy to understand. Fuzzy logic is a more sensitive approach without the complexity.
2. Fuzzy logic is flexible: In any given system, it is easy to coat on more functionality without being start from scratch.
3. Fuzzy logic is tolerable about inexact data: In the nature or in any experimental process everything is inexact. Fuzzy logic is made tolerable about all these things.
4. Fuzzy logic is able to model nonlinear functions of random complexity: A fuzzy controller is able to match any kind of input and output values. This process is made mainly easy by adaptive techniques which are available in Fuzzy Logic Toolbox of MATLAB software like Adaptive Neuro-Fuzzy Inference Systems (ANFIS).
5. Fuzzy logic is based on general language: Fuzzy logic allows us to communicate with the system using a common language of human like “If-then”.
The function of Fuzzy inference system is to interpret the values from the input vector and using some set of rules, assigns these values to the output vector. This definition is clear from the figure

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