Impact of the Statistical Properties the Input Data for Mathematical Models in a Digital Twin Environment

The paper deals with the problem of evaluating the statistical properties of the input data in Automated Process Control Systems when used in simulation and digital twin environment. In modern real-time digital systems mathematical methods have been used increasingly to generate hybrid models of control systems, one of which problems is the compatibility of input data. We have studied the statistical properties of the digital system input data flow in the digital twin environment of the control system in order to determine the possibility of describing the specified data using standard distributions. Studies were conducted both at the level of individual packets and for averaged data. As a result, it is shown that a description of the input data properties using standard distributions is possible when averaging network packets over about seconds. The results can be used to generate mathematical models of real-time digital systems.