Development of digital twin for PMDC motor control loop

Abstract

Recent developments in the digital domain can reduce the resources needed for efficient plant control. The growth of cloud computing and big data analysis has paved the way for using digital domain as processing units. Metaverse is the animated version of the physical realm in digital domain. The control mechanism and dynamics of the real-world data cannot be manually fed to the digital domain. The real plant can change its dynamics during its operation which the previously modeled mathematical model cannot address. So, the model for the system needs to be developed by its own and it need to be adaptable. This can be done by implementing the digital twin. In this work, a nonlinear Auto Regressive Exogenous model captures the dynamics of a PMDC motor. A model predictive approach is used to control the PMDC motor, which uses updated model to predict the response and generate the desired control input.