Fuzzy logic

6.1. IMPORTANCE OF FUZZY LOGIC Fuzzy logic is all about the relative importance of precision: use as Fuzzy Logic Toolbox software with MATLAB technical computing software as a tool for solving problems with fuzzy logic. Fuzzy logic is a fascinating area of research because it does a good job of trading off between significance and precision something that humans have been managing for a very long time. In this sense, fuzzy logic is both old and new because, although the modern and methodical science

Introduction Fuzzy system has been applied to various type of application or system. Fuzzy system is an approach of the computational intelligence use a collection of fuzzy functions and rules to reason about a data. Its use any Fuzzy Logic based system which use Fuzzy Logic as basic for knowledgeable representation using different forms of knowledge. The main function of fuzzy logic technology is it ability of propose an approximate solvent to an imprecisely formulated problem. Fuzzy Logic in other

4. FUZZY LOGIC CONTROLLER 4.1 Introduction Fuzzy Logic provides a completely different approach. One can concentrate on solving the problem rather than trying to model the system mathematically, if that is even possible. This almost invariably leads to quicker, cheaper solutions. Once understood, this technology is not difficult to implement and the results are usually quite surprising and more than satisfactory. Fuzzy logic is a complex mathematical method that allows solving difficult simulated

Chapter 2 2.1 Fuzzy Logic Controller Fuzzy logic is a type of multi valued logic. It deals with approximate reasoning rather than precise. Fuzzy logic derived from fuzzy set theory. Fuzzy logic was first proposed by Lotfi Zadeh in 1965. Fuzzy logic has currently used in control theory, artificial intelligence systems specially to control complex aircraft engines and control surfaces, helicopter control, messile guidance, automatic transmission, wheel slip control

assessment of the power system. 1. Fuzzy Logic: The Fuzzy logic system (FLS) is a logic system which represents reasons and knowledge in a fuzzy manner for reasoning under uncertainty or describes in imprecise manner for human interpretation. Not like Boolean logic and classic logic which assumes that entire fact is either true or false, but fuzzy logic allows Boolean logic to tackle with vague and imprecise expressions of human understanding. Not like the classic logic systems, it models the reasoning

Networks, Multi Agent Systems and Fuzzy Logic approaches

Review L.A. Zadeh, Fuzzy Sets [33] In 1965 the concept of fuzzy logic was first introduced by the Professor Lotfi A. Zadeh in the University of California, Berkeley [33]. Fuzzy logic is a powerful design system for implementing the artificial intelligence in the controller which provides simple and intuitive method for software engineers to implement logic in complex systems. This concept had been given in one amongst his research papers under the name Fuzzy logic or Fuzzy sets. George J. Kilr

value of “0” or “1” under Boolean logic. While under fuzzy logic an input has been associated a certain qualitative ranges. Fuzzy logic allows one to deduce outputs from fuzzy inputs. Fuzzy logic is a technique for mapping inputs to outputs called curve fitting. Advantages of fuzzy logic is the absence of a need for a mathematical model for mapping inputs to outputs and also the absence of a need for precise or noise free inputs. Properly designed fuzzy logic systems with genetic conditioning can

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 [65]. 4.1 FUZZY LOGIC SYSTEM A fuzzy logic system (FLS) can be defined as the nonlinear mapping

Fuzzy Logic Technique for PQ Improvement by UPQC for Renewable Energy Recourse’s 1BJ SHIVA RAMA KRISHNA RAO, PG STUDENT, BRILLIANT GROUP OF INSTITUTIONS, HYD 2O SWATHI, PG STUDENT, BRILLIANT GROUP OF INSTITUTIONS, HYD 3B. NAGI REDDY, ASST.PROF, BRILLIANT GROUP OF INSTITUTIONS, HYD ABSTRACT: -- In this a fuzzy logic control technique has been proposed for power quality improvement by using UPQC The UPQC is controlled to regulate the WF terminal voltage, and to mitigate voltage fluctuations at