This article presents the design, implementation, and validation of a real-time digital twin for a Stewart platform, integrated with advanced trajectory computation capabilities. Stewart platforms, known for their high precision and multi-degree-of-freedom motion, are widely used in applications such as flight simulators, medical devices, and manufacturing systems. The integration of a digital twin allows for real-time monitoring, predictive analysis, and enhanced control, thereby improving the system's operational efficiency and resilience. This work details the architectural framework of the digital twin, the methods for real-time data synchronization, the algorithms for dynamic trajectory generation, and the validation of the virtual model against the physical Stewart platform. The proposed system demonstrates significant potential for improving the control, diagnostics, and overall performance of complex robotic manipulators through a comprehensive virtual representation.

Digital Twin, Stewart Platform, Real-Time Control

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