The objective of the integrated course is to provide the students with the advanced methodological tools for the analysis of dynamic systems in the discrete-time domain, both in a deterministic (the 3 ECS module “DIGITAL SYSTEMS”, code 454MI-2) and in a stochastic setting (the present 6 ECS module “DATA-DRIVEN DIGITAL SYSTEMS”, code 454MI-1). Specifically, the present module addresses the analysis and design of estimation, prediction, and identification algorithms using experimental data, as well as the design and implementation of state estimation algorithms in deterministic and stochastic frameworks. As a whole, the integrated course 454MI, made of 454MI-1 and 454MI-2, is designed as a complement to the course of Fundamentals of Automatic Control offered in the second year of the degree courses, since it is focused on the discrete-time context, which is more suitable to address topics in ICT and data management. The course extends the knowledge base to include estimation and identification techniques from experimental data and addresses practical implementation aspects. The course is suitable for 4th year students, both in the industrial context and in the ICT and data management framework. The present 6 ECS module is the second within the logical flow of the entire integrated course with code 454MI—the topics concern stochastic discrete-time systems, with emphasis on estimation and identification methodologies based on experimental data.
- Teacher: GIANFRANCO FENU