Oksana Porubay
@tuit.uz
Information Technology/Computer Engineering
ashkent University of Information Technologies named after Muhammad al-Khwarizmi
RESEARCH, TEACHING, or OTHER INTERESTS
Multidisciplinary
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Scopus Publications
Oksana Porubay, Isamiddin Siddikov, Gulruxsor Nashvandova, and Gulchexra Alimova
AIP Publishing
Isamiddin Siddikov, Oksana Porubay, and Temurbek Rakhimov
Institute of Advanced Engineering and Science
Real-acting objects are characterized by the presence of various types of random perturbations, which significantly reduce the quality of the control process, which determines the use of modern methods of intellectual technology to solve the problem of synthesis of control systems of structurally complex dynamic objects, allowing to compensate the influence of external factors with the properties of randomness and partial uncertainty. The article considers issues of synthesis of the automatic control system of dynamic objects by applying the theory of intelligent control. In this case, a neural network based on radial-basis functions is used at each discrete interval for neuro-fuzzy approximation of the control system, allowing real-time adjustment of the regulator parameters. The radial basis function is designed to approximate functions defined in the implicit form of pattern sets. The neuro-fuzzy regulator's parameter configuration is accomplished using a genetic algorithm, enabling more efficient computation to determine the regulator's set parameters. The regulator's parameters are represented as a vector, facilitating their application to multidimensional objects. To determine the optimal tuning parameters of the neuro-fuzzy regulator, characterized by high convergence and the possibility of determining global extrema, a genetic algorithm was used. The effectiveness of the neuro-fuzzy regulator is explained by the possibility of providing quality control of the dynamic object under random perturbations and uncertainty of input data.
I. Kh. Siddikov and O. V. Porubay
AIP Publishing
Oksana Porubay, Isamiddin Siddikov, and Khasanova Madina
IEEE
The paper considers the issues of optimizing the modes of electric power systems based on the methods of intelligent technologies: evolutionary and ant algorithms, taking into account the features of the object under consideration. An optimization criterion has been formulated, which includes minimizing the total cost of fuel in electric power facilities. The main restrictions imposed by the dynamics of the functioning of technological units and their mode of operation are determined. These restrictions are presented in the form of a system of linear equations that characterize the steady state of the units, as well as in the form of inequalities, which are the limiting restrictions on the parameters of the generated electricity. To solve this problem, evolutionary modeling algorithms and an ant colony algorithm have been developed. A comparative analysis of these algorithms was carried out in order to determine their capabilities and scope. The use of evolutionary algorithms in problems with discrete values of variables does not require any assumptions and simplifications of the problem. When solving the problem of optimal placement and determination of the parameters of compensating devices and linear regulators, it was possible to reduce losses in the system by 3.5%.
I Siddikov, O Porubay, and O Mirjalilov
IOP Publishing
Abstract The work contains the results of the analysis of studies that were carried out to improve the operating modes of power facilities, taking into account uncertain data and the possibility of changing the load. A mathematical model of energy objects is formulated taking into account various types of restrictions. A comparative analysis of methods for solving problems was carried out and a method based on a penalty matrix was chosen. The results of the experiment showed the effectiveness of the proposed method for optimizing the modes of power facilities during changes in loads in different periods.
Isomiddin Siddikov and Oksana Porubay
EDP Sciences
The article is devoted to the issue of creating a mathematical model of the problem of making management decisions in electric power facilities based on modern intelligent technologies, which makes it possible to take into account the influence of various factors on the operating modes of the power system. A systematic approach to describing processes in the mathematical language of the theory of fuzzy sets is proposed. To solve the problem of controlling the operating modes of the power system, a neurofuzzy network has been developed that combines the algorithms of Takagi-Sugeno fuzzy inference, as well as a recurrent neural network. An adaptive learning algorithm based on the Frechet method is proposed for training a neural network. The analysis of the efficiency of the fuzzy control model under the conditions of various modes of functioning of the local power system is carried out.
Oksana Porubay
IEEE
Despite the fact that “wavelet theory” was many times considered by scientists and the whole scientific direction connected with wavelet theory appeared recent years, it is still impossible to say exactly what wavelet is and what function are called wavelet function. Wavelets can be orthogonal Semiorthogonal and biorthogonal. These functions may be symmetrical, asymmetrical and unbalanced. This article details the concept of “wavelet” are examples of different wavelets, the application of wavelet transforms, as well as a comparison of different wavelet - transformations in compression information.