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This article deals with the management of a Freescale small robotic car along the predefined guide line. Controlling of the direction of movement of the robot is performed by neural networks, and scales (memory) of neurons are calculated by Hebbian learning from the truth tables as learning with a teacher. Reflexive infrared sensors serves as inputs. The results are experiments, which are used to compare two methods of mobile robot control - tracking lines.

The article deals with different procedures for determining the safety integrity level and its applications. The purpose of this research was to evaluate the system and associate it with certain safety integrity level. In this article, we will use IEC 61508, IEC 61511 and IEC 62061 for comparison. The first standard is specified as the superior standard for all safety-critical systems. The second one acts as an extension of the superior standard in the field of functional safety. The last one is aimed at machinery safety.

The paper deals with differential equation of the second order containing a small parameter at the highest derivative, studying various oscillation patterns occurring in the system, numerically modelling the results in MATLAB built-in solver using the Runge-Kutta method. The mathematical base is provided in the theory of singular perturbations, briefly described as well.