â  abstract: in this paper, artificial neural network (ann) was used for modeling the nonlinear structure of a debutanizer column in a refinery gas process plant. the actual input-output data of the system were measured in order to be used for system identification based on root mean square error (rmse) minimization approach. it was shown that the designed recurrent neural network is able to pr...

in this paper, we describe our implementation of an interior point algorithm for large scale systems. first we identify system with small and medium methods convex optimization, then we use interior point method for identification. finally we offer an interior point method that uses nonlinear cost function and see that we achieve a good trade-off between error and cpu time. actually, in this pa...

In this paper, we propose a novel approach for the data-driven characterization of power system dynamics. The developed method Extended Subspace Identification (ESI) is suitable systems with output measurements when all dynamics states are not observable. It particularly applicable dynamic identification using Phasor Measurement Units (PMUs) measurements. As in case systems, it often expensive ...

Abstract when the conventional system classifies power distribution data, data category is not fine enough, resulting in low accuracy of abnormal identification, high false detection rate and large correction error. A identification processing based on correlation classification proposed. In terms hardware, multi-layer framework adopted, overall hardware structure composed communication modules...

The accurate peak power estimation of a battery pack is essential to the power-train control of electric vehicles (EVs). It helps to evaluate the maximum charge and discharge capability of the battery system, and thus to optimally control the power-train system to meet the requirement of acceleration, gradient climbing and regenerative braking while achieving a high energy efficiency. A novel o...

An indirect adaptive fuzzy power system stabilizer (IDFPSS) is proposed in this paper. It consists of A fuzzy identifier and a feedback linearizing controller. The objective is to damp local and inter-area oscillations that occur following power system disturbance. The effectiveness of the proposed technique is illustrated by applying the IDFPSS to a two-area four-machine system that is typical...