DETERMINATION OF CONTROL OBJECTS DYNAMIC PARAMETERS IN REALTIME MODE USING GRAPHO-ANALYTICAL METHODS OF IDENTIFICATI

Abstract

The article explores the possibility of using modern hardware and software to automate traditional methods of identification, with the ability to obtain the values of the parameters of control objects in real time. The known graph-analytical methods of identification of control objects are analyzed and the inexpediency of their use in real-time identification due to the need for manual input of experimental data is proved. To determine the dynamic parameters of typical linear objects of automatic control systems, it is proposed to use the rate of change of the output signal of the researched object. It is proved that the use of software packages Mathcad and Matlab allows to directly calculate the rate of change of the output signal of the control object, which significantly reduces data processing time, and the use of Matlab environment, thanks to the built-in OPC server, allows real-time mode analysis of process data obtaining from sensors or digital network controllers. The block diagram of the system for the research of the proposed method for determining the dynamic characteristics of the control object and the block diagram of the algorithm for calculating the dynamic parameters of the control object are proposed. An example of identification of a first-order control object using the rate of change of the output signal is given. Experimentally determined values of the controlled parameter (temperature) were recorded by a sensor connected to the analog input of the Oven PLC63 controller. Data from the controller over the Modbus network was transmitted via a universal OPC – Master OPC server on a personal computer. The Matlab environment was used as the OPC client, where the dynamics parameters of the researched object were calculated. It is proved that the proposed method can significantly increase the efficiency of known graph-analytical methods of identification. It was found that the noise present in the sensor signals can significantly affect the accuracy of determining the parameters of the control object, so to reduce the influence of these noises, it is necessary to use low-pass filters.