Accurate computation of harmonics is really a challenging problem in power system. Many algorithms have been proposed for harmonic estimation. In this paper a novel hybrid approach is proposed to estimate the amplitudes and phases of fundamental, third and fifth harmonics of three different types of distorted power signals in presence of white noise. A robust estimator known as H∞ Filter is use...

Neurules are a kind of hybrid rules integrating neurocomputing and production rules. Each neurule is represented as an adaline unit. Thus, the corresponding rule base consists of a number of autonomous adaline units (neurules). Due to this fact, a modular and natural rule base is constructed, in contrast to existing connectionist rule bases. In this paper, we present a method for generating neu...

A new artificial neural network (ANN) has been created, similar to the ADALINE-type network, with linear activation function and bubble error sorting, designed to recognise and classify pneumatically-spliced yarn joints. In the second part of the article, the effectiveness of recognition and classification of the proposed ANN will be presented.

An adaptive unstructured grid generation scheme is introduced to use finite volume (FV) and finite element (FE) formulation to solve the heat equation with singular boundary conditions. Regular grids could not acheive accurate solution to this problem. The grid generation scheme uses an optimal time complexity frontal method for the automatic generation and delaunay triangulation of the grid po...

The phase synchronization control technique of shunt active power filter (SAPF) is discussed in this article. Due to the harmful effects harmonic currents on systems, issue decreasing their has generated a lot research. A SAPF acknowledged as most dependable instrument area. will detects current harmonics present system and also generates injects corrective mitigation reduce harmonics. This imp...

By expanding a function in series form it can be represented to an arbitrary degree of accuracy by taking enough terms. It is therefore possible, in principle, to conduct a linear regression on a new set of variables, transformed by a fixed mapping. This leads to a large computational burden and to the need for an infeasible amount of data from which the coefficients must be estimated and is no...

an adaptive version of growing and pruning rbf neural network has been used to predict the system output and implement linear model-based predictive controller (lmpc) and non-linear model-based predictive controller (nmpc) strategies. a radial-basis neural network with growing and pruning capabilities is introduced to carry out on-line model identification.an unscented kalman filter (ukf) algor...

Recently, we have proposed the minimum error entropy (MEE) criterion as an information theoretic alternative to the widely used mean square error criterion in supervised adaptive system training. For this purpose, we have formulated a nonparametric estimator for Renyi’s entropy that employs Parzen windowing. Mathematical investigation of the proposed entropy estimator revealed interesting insig...