This paper describes a fuzzy logic based slip controller for an induction motor, with efficiency optimization for steady state operation. The speed control is accomplished through a Mandani type fuzzy controller, with 11 rules, taking speed error (built with 5 Membership Functions M.F.) and speed error variation (3 M.F.) as inputs, to produce the slip increment (5 M.F.). The average motor input...

Controlling of DC-DC converter is vital task in power conversion. DC-DC converters are used in many applications like solar charger, computer power supplies, switching mode regulators, aircrafts etc. Focus of this paper is to model a controlling system for buck converter which controls output of buck converter constant instead of changing load and input supply to buck converter. Controlling met...

The paper describes a variable speed wind generation system where fuzzy logic principles are used for efficiency optimization and performance enhancement control. A squirrel cage induction generator feeds the power to a double-sided pulse width modulated converter system which pumps power to a utility grid or can supply to an autonomous system. The generation system has fuzzy logic control with...

comparing the performance of a set of activities or organizations under uncertainty environment has been performed by means of fuzzy data envelopment analysis (fdea) since the traditional dea models require accurate and precise performance data. as regards a method for dealing with uncertainty environment, many researchers have introduced dea models in fuzzy environment. some of these models ar...

Genetic fuzzy rule selection is an effective approach to the design of accurate and interpretable fuzzy rule-based classifiers. It tries to minimize the complexity of fuzzy rule-based classifiers while maximizing their accuracy by selecting only a small number of fuzzy rules from a large number of candidate rules. One important issue in genetic fuzzy rule selection is the prescreening of candid...

This work describes experiments carried out using fuzzy formal concept analysis for the generation of fuzzy classification rules to be used by a genetic process. These rules are simply the intention of the formal concepts extracted from a fuzzy-based formal context. The motivation we have is the need for a method to generate fuzzy classification rules to be used as the search space of the genet...

De-interlacing algorithms realize the interlaced to progressive conversion required in many applications. The most cost efficient are intra-field techniques, which interpolate pixels of the same field. Some of these methods use the upper and lower line pixels. Among them, the ELA algorithm is widely employed since it reconstructs the edges of the de-interlaced image with more accuracy eliminati...

In this paper, the variational iteration method for solving nth-order fuzzy integro differential equations (nth-FIDE) is proposed. In fact the problem is changed to the system of ordinary fuzzy integro-differential equations and then fuzzy solution of nth-FIDE is obtained. Some examples show the efficiency of the proposed method.

In this paper the questions of defining the optimum allocation of centers in fuzzy transportation networks are observed by the minimax criterion. It is supposed that the information received from the geographical information system is presented as a fuzzy graph. In this case the task of defining optimum allocation of the centers transforms into the task of defining the fuzzy set of graph bases....

A new multiobjective selection procedure for Genetic Algorithms based on the paradigms of fuzzy logic is discussed and compared to the niched Pareto selection procedure. In the example presented here the fuzzy logic procedure optimized the parameters of a series of functions in a more efficient manner than the niched Pareto approach. The main advantage that the fuzzy logic approach has over the...