Modeling and implementation of a real-time digital twin for the Stewart platform with real-time trajectory computation

The concept of a digital twin is increasingly acknowledged as an innovative and promising tool with significant potential in various end-use applications. At the heart of digital twin technology is the acquisition of real-time data from physical entities. However, the occurrence of disturbances necessitates the incorporation of resilience features within the digital twin architecture. The primary objective of this article is to develop resilient digital twins specifically for the Stewart platform. This work focuses on constructing the virtual component of the digital twin using MATLAB/Simulink and subsequently integrating this virtual model with its physical counterpart to establish a comprehensive digital twin system. Unlike other models, this system includes a motion trajectory computation module. This module is designed to receive signals from physical entities and convert them into motion trajectory data for input into the model, thereby aiming to accurately reflect the state of the physical entities under disruptive conditions. This functionality significantly enhances the reliability of the system beyond that of traditional digital twin systems. Furthermore, the article explores novel strategies and a framework for enhancing the resilience of the Stewart platform to disturbances.