MODELING AND SIMULATION OF DYNAMIC SYSTEMS IN THE FUNCTION OF BASIC RESEARCH IN TECHNICAL AND TECHNOLOGICAL SCIENCES.

The model, as a synthetic abstraction of reality, is applied in engineering practice to study the characteristics and behavior of dynamic systems. The paper gives an example of a simple physical model of an aircraft. A mathematical model is defined for testing primary flight characteristics. The paper uses a predictive model that is used to analyze the consequences of different system management strategies. The predictive model connects dependent and independent variables that describe system states. The paper presents simulations on three models. Mathematical and statistical methods are used in the paper. Parametric statistical methods are based on the normal distribution when predicting certain phenomena with a certain probability. The simulations in this paper represent the execution of operations on the system model in order to obtain the desired knowledge about the system’s behavior. This is a simple and safe way to experiment with a model. A real dynamic system whose movement is described with twelve differential equations is considered. The complexity of the problem of solving differential equations requires the use of the Runge-Kutta method of the fourth order. These simulations enable the understanding of the movement of complex dynamic systems, the design of new ones and the improvement of the performance of existing systems. A special contribution of the paper is in the large savings of all resources. The contribution of the paper itself is in confirming that the role of simulation in scientific research is indispensable due to: better understanding of the system (it reveals oversights in design), improving efficiency (it reveals problems in systems), testing alternatives (it avoids costly and sometimes dangerous trial and error experimentation on the real system), saving time, human resources and money (the cost of simulation is small compared to the gain it gives), and creating virtual environments. [ABSTRACT FROM AUTHOR]