This study presents an innovative methodology for the development and testing of a digital twin for an Unmanned Aerial Vehicle (UAV), effectively bridging the simulation-reality gap. The proposed approach integrates Model-in-the-Loop (MiL) and Hardware-in-the-Loop (HiL) testing, enabling a comprehensive evaluation of the UAV’s digital twin in simulated environments. Behavioral testing includes open-loop scenarios, baseline feedback controllers, and Model Predictive Control (MPC). The UAV’s dynamic model is simplified and rigorously validated through experimental verification, ensuring high fidelity and reliability. Furthermore, this approach facilitates the critical transition from simulation to real-world experimentation by providing a robust framework for evaluating UAV performance under realistic conditions. This methodology highlights the importance of experimental validation in replicating real-world scenarios, ensuring the robustness and accuracy of the digital twin.
