This thesis develops a Digital Twin (DT) engineering approach inspired by systems theory to facilitate the management of complex systems in an increasingly interconnected world. The DT stands out for its ability to combine data-driven and model-based approaches, integrating technologies such as the Internet of Things, simulation, Big Data and artificial intelligence to create a virtual replica of a physical system, enabling monitoring, prediction, and optimization of its performance. The proposed DT engineering framework is conceptual, formal, and operational, structuring the modeling and synchronization processes between the twin and its real system. This framework includes a formal specification and a unified conceptual model to ensure the accuracy and reliability of the DT, along with a modular architecture that simplifies its design and deployment while addressing the issue of synchronization in depth. A DT prototype applied to mobility on the University of Bordeaux campus illustrates this methodology, providing a sensitivity analysis of synchronization parameters and demonstrating the potential of this engineering approach for practical applications.
