This course introduces the principles of model identification for
non-linear dynamic systems, and provides a set of possible solution
methods that are thoroughly characterized in terms of modelling
assumptions and uncertainty levels. The course is intended to provide the mathematical tools to model, identify and predict the state and behaviour of complex systems, based on a set of experimental measurements and observations.
- Teacher: Guglielmo Frigo
- Teacher: Mario Paolone
