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The Control Mode Identification Using Structural-Parametric Time Series Analysis

The study of the properties and features of objects using modern methods of information processing is based on the construction of a mathematical model of the object under study based on the observed data. Quite often, in various application areas, there is not a prior information about the structure and parameters of objects and control systems. To understand the features of the operation of control systems to create an adequate model, it becomes necessary to identify the control action from experimental data. During the operation of complex systems, the control action can vary significantly depending on external and internal (for example, the appearance of defects) factors. Using a large amount of data, artificial intelligence methods, as well as the capabilities of modern computing tools, it becomes possible to identify hidden patterns that have a different temporal hierarchy. In this paper, it is proposed to use the method of structural-parametric analysis of time series to identify the modes of the control action. Examples of the use of this method for biological and technical systems are given. The effectiveness of using the approach for the analysis of complex structured data is demonstrated.