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All Journal Jurnal Informatika International Journal of Advances in Intelligent Informatics
Roman Voliansky
Igor Sikorsky Kyiv Polytechnic Institute
Computer Science & IT

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Parallel mathematical models of dynamic objects Roman Voliansky; Andri Pranolo
International Journal of Advances in Intelligent Informatics Vol 4, No 2 (2018): July 2018
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/ijain.v4i2.229

Abstract

The paper deals with the developing of the methodological backgrounds for the modeling and simulation of complex dynamical objects. Such backgrounds allow us to perform coordinate transformation and formulate the algorithm of its usage for transforming the serial mathematical model into parallel ones. This algorithm is based on partial fraction decomposition of the transfer function of a dynamic object. Usage of proposed algorithms is one of the ways to decrease calculation time and improve PC usage while a simulation is being performed. We prove our approach by considering the example of modeling and simulating of fourth order dynamical object with various eigenvalues. This example shows that developed parallel model is stable, well-convergent, and high-accuracy model. There is no defined any calculation errors between well-known serial model and proposed parallel one. Nevertheless, the proposed approach’s usage allows us to reduce calculation time by more than 20% by using several CPU’s cores while calculations are being performed.
Transformation of the generalized chaotic system into canonical form Roman Voliansky
International Journal of Advances in Intelligent Informatics Vol 3, No 3 (2017): November 2017
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/ijain.v3i3.113

Abstract

The paper deals with the developing of the numerical algorithms for transformation of generalized chaotic system into canonical form. Such transformation allows us to simplify control algorithm for chaotic system. These algorithms are defined by using Lie derivatives for output variable and solution of nonlinear equations. Usage of proposed algorithm is one of the ways for discovering of new chaotic attractors. These attractors can be obtained by transformation of known chaotic systems into various state spaces. Transformed attractors depend on both parameters of chaotic system and sample time of its discrete model.
Transformation of the generalized chaotic system into the discrete-time complex domain Nina Volianska; Roman Voliansky; Oleksandr Sadovoi
Jurnal Informatika Vol 15, No 1 (2021): January 2021
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jifo.v15i1.a20222

Abstract

The paper deals with the development of the backgrounds for the design and implementation of secured communications by using systems with chaotic dynamics. Such backgrounds allow us to perform the stable transformation of a nonlinear object into a simpler form and formulate the nonlinearities simplification optimization algorithm. This algorithm is based on the optimization problem's solution, which makes it possible to define polynomial order, approximation terms, and breakpoints. Usage of proposed algorithms is one of the ways to simplify known chaotic system models without neglecting their unique properties and features. We prove our approach by considering simplifying the Mackey-Glass system and transforming it into a discrete-time complex domain. This example shows that the transformed system produces chaotic oscillations with twice-increased highest Lyapunov exponent. This fact can be considered as improving the unpredictability of the transformed system, and thus it makes background to make highly non-intercepted and undecoded transmission channels.
Co-Authors Achmad Fanany Onnilita Gaffar Andri Pranolo Malani, Rheo Nina Volianska Oleksandr Sadovoi Suprapty, Bedi