Mathematical models with analytical properties are needed to create modern stabilization systems for various objects and technical systems. This is due to the fact that most of the existing methods for the synthesis of automatic systems are based on mathematical transformations of models of control objects. However, for complex objects and systems, these models are obtained experimentally. Moreover, the experimental data are approximated by various well-known methods. If the dependences are essentially nonlinear in nature, they are approximated by sections. Such a fragmented model as a whole is not analytical, which excludes the use of many well-known methods for the synthesis of nonlinear stabilization systems. In these cases, it is advisable to use the new Cut-Glue approximation method developed at DSTU, which allows one to obtain an analytical model of an object from piecewise approximations. This analytical model allows you to apply the analytical method for the design of quasilinear control systems for nonlinear objects. In this paper the propoused approach is illustrated by example of the design of a nonlinear system for stabilizing the flight altitude of an airship.

Keywords: stabilization system, analytical synthesis, nonlinear control object, mathematical model, quasilinear form, experimental data, fragmentary model, multiplicatively additive approximation

In this paper, we describe three target distribution methods for vehicle group control. The purpose of the methods being developed is to increase the number of defenders who survived after the fight with the enemy. The first method introduces a priority system based on the distance to the robot, as well as the distance to the protected area. The second method is based on the application of the modified swarm particle method, and the third method is based on the evolutionary-genetic algorithm. To demonstrate the work of each method, software was developed in C # and Python. The performed simulation showed the effectiveness of each method developed. Sixty experiments were carried out, 3 parameters were evaluated in each experiment. The best results were achieved using a method based on the priority system.

Keywords: vehicle, group control, priority, target distribution, optimization, particle swarm optimization, evolutionary-genetic algorithm, heuristic method