Online Control Method of DC Motor Based on Digital Twin Architecture in Network Environment

With the continuous development of information technologies, the digital twin has become one of the hot spots in recent years. In a digital twin system, the mathematical model of the control plant is mostly obtained from the derivation and computation of the mechanism model in the current remote virtual simulation. But in physical systems, the parameters primarily depend on the state of the system. A mathematical model for a physical system with time-varying characteristics is therefore inappropriate. Simultaneously, based on online identification and prediction, experiments were developed to carry out interdisciplinary comprehensive experimental education and conform with the growth of the engineering disciplines. In this paper, an online DT-based DC motor system is present. A five-dimension model of the DT system is designed and implemented with the physical DC motor system, DT 3D model, mathematical model, real-time data, and the online DT platform. The model parameters can be calculated and the future state can be predicted using the online identification and prediction method. Experiments show the stability of the DT architecture. The DT-predicted output can be consistent with the physical device output. Additionally, under certain circumstances, DT systems can take the place of the physical data in order to maintain the system's functionality.