International Scientific Journals
of Scientific Technical Union of Mechanical Engineering "Industry 4.0"

In this paper, it was proposed the experimental identification of the mathematical model of the DC motor, coupled with a reaction wheel. It was proposed to approximate the experimental curve with the mathematical model of order 2 inertia, identified by Genetic Algorithm. To estimate the mathematical model of the control object it was proposed to use the Genetic Algorithm method, the results obtained were compared with the Strejc methods and the results obtained using the Process Models module from System Identification Toolbox from MATLAB.

This paper presents, general formulation and new solution to actual scientific and applied task of developing new methods of the high voltage distribution networks reconfiguration based on mathematical devices of genetic algorithms, that provide additional reduction of electricity losses and its quality improvements, when increasing 6 (10 ) kV networks to 20 kV voltage class. New method of the electrical power distribution network reconfiguration at normal mode was developed using of genetic algorithms, which on the basis of electrical power network modes enables determination of an optimal scheme configuration so that losses of power transportation were minimal provided that standard quality of electric power with voltage at consumers’ connection points assured and minimum connectedness of electrical power network  scheme and minimal economic losses from power underproduction maintained.

This paper has presented chaos synchronization in the Duffing system using the backstepping approach. Backstepping approach consists of parameters which accept positive values. The parameters are usually chosen optional. The system responses are differently for each value. It is necessary to select proper parameters to obtain a good response because the improper selection of the parameters lead to inappropriate responses. Genetic algorithm can select appropriate and optimal values for the parameters. GA by minimizing the fitness function can find the optimal values for the parameters. This selected fitness function is for minimizing the least square error. Fitness function forces the system error to decay to zero rapidly that it causes the system to have a short and optimal setting time. Fitness function also makes an optimal controller and causes overshoot to reach to its minimum value. This hybrid makes an optimal backstepping controller.

The paper highlights some approaches to fundamental problems of intelligent control of autonomous underwater vehicles (AUV) groups: logic-based approach to task management for inspection and protection of the water area, hybrid evolutionary models and algorithms for dynamic mission planning, and methods for rigorous analysis of discrete-continuous models of AUVs formations with discrete-event approach to AUV’s operational modes switching. Hierarchical three-level architecture of control system is supposed and various models of AUV group functioning at the different control levels are considered.