Browsing by Author "Tkalenko, Oleksandr"

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Analysis and Design of the Interval Optimal Electromechanical Systems
(ScientificWorld-NetAkhatAV, Karlsruhe, Germany, 2025) Voliansky, Roman; Kuznetsov, Vitaliy V.; Metelenko, Natalia; Kovalenko, Viktor; Spirintsev, Dmytro V.; Babyak, Mykola O.; Tryputen, Mykola; Tkalenko, Oleksandr; Halushko, Dmytro
ENG: The monograph has been prepared as part of comprehensive scientific research aimed at improving energy efficiency, digitalization, and the development of intelligent control systems. The materials presented reflect the results of many years of interdisciplinary research carried out with the participation of specialists from various scientific schools and universities. They provide a holistic understanding of modern trends in electric drive system control and form a scientific and practical basis for introducing innovative solutions in industry and transport. The discussed concepts of optimization, robust control, and the integration of renewable energy sources are closely linked to the transition to sustainable energy, automation of production processes, and infrastructure digitalization. Special attention is given to interaction with international research programs, which allows the use of advanced experience from Germany, Japan, the USA, and other countries in the field of digital twins, the industrial Internet of Things (Industrial IoT), andcyber-physical control systems.
Control of Drum Shear Electric Drive Using Self-Learning Artificial Neural Networks
(MDPI, Basel, Switzerland, 2025) Batyrbek, Alibek; Kuznetsov, Valeriy; Kuznetsov, Vitalii V.; Rojek, Artur; Kovalenko, Viktor; Tkalenko, Oleksandr; Tytiuk, Valerii; Krasovskyi, Pavlo
ENG: The objective of this work was to study the possibility of upgrading the control system of the drum shear mechanism by using neural network PI controllers to improve the efficiency of the sheet-metal cutting process. The developed detailed model of the mechanism, including a dual DC electric drive with three subordinate control loops for the voltage of the thyristor converter, current and speed of the motors, a 6-mass kinematic system with viscoelastic connections as well as a model of the metal cutting process, made it possible to uncover that the interaction of electric drives with the mechanical part leads to significant speed fluctuations during the cutting process, which worsens the quality of the sheet-metal edge. A modified system of current and speed controllers with built-in three-layer fitting neural networks as nonlinear components of proportional-integral channels is proposed. An algorithm for the fast learning of neural controllers using the gradient descent method in each cycle of calculating the controller signal is also proposed. The developed neuro-regulators make it possible to reduce the amplitude of speed fluctuations during the cutting process by four times, ensuring the effective damping of oscillations and reducing the duration of transient processes to 0.1 s.
Numerical Models of Novel Discrete-Time Chaotic Systems
(CEUR-WS Team, Aachen, Germany, 2025) Voliansky, Roman; Volianska, Nina; Yakovenko, Vitaly; Tkalenko, Oleksandr; Kuznetsov, Vitalii V.
ENG: The paper proposes a theoretical approach to designing novel dynamical systems based on known discrete maps. We show some algebraic transformations based on the derivative operators' discrete-time approximation. These operators' approximations are considered as defined by some nonlinear algebraic combinations of finite and infinite element numbers of maps. Such an approach allows us to use various differential operators, including fractional-order and complex fractional-order ones. As a result, matrix nonlinear algebraic equations are defined for the considered discrete map. The order of these equations depends on the number and order of the derivatives used to define the system dynamics. Such a formalized approach allows us to easily define the system's finite-difference equations and solve them using known numerical methods. The obtained solutions make it possible to determine the systems' motions, and we offer to add some external signals to increase the range where these motions are defined. One can consider such signals from a control theory viewpoint as control one and use known control approaches to define system equations in various state spaces. Using one of these approaches allows us to significantly increase the number of system outputs by using observability equations for defined system state variables. We show the use of our approach by designing and studying several chaotic systems based on a well-known logistic equation. Our studies prove the possibility of constructing novel systems that produce previously unknown chaotic signals significantly different from known ones. The given system equations not only allow the generation of new signals for use in various applications but also give us the possibility to improve system performance.
Scientific Basis of Analysis and Synthesis of Optimal Energy-Efficient Control of Electromechanical Systems
(ScientificWorld-NetAkhatAV, Karlsruhe, Germany, 2024) Voliansky, Roman; Kuznetsov, Vitaliy V.; Doskoch, Volodymyr; Tkalenko, Oleksandr
ENG: The authors' achievements in the field of development of control systems theory, where high-order sliding modes are implemented, was presented. Original methods for optimizing the accuracy of automatic - control systems for electric drives with nonlinear activation functions were outlined. The dynamic and static characteristics of control systems with nonlinear control algorithms were considered, and their stability was analyzed. For scientific and technical workers engaged in the research, design and operation of modern automatic control systems, as well as for students and post-graduate students of relevant specialties.