Research & Publications

My research lies in the wide field of (mostly linear) dynamical model approximation, control design and analysis.  The methods and numerical tools I develop are not dedicated to a particular application; rather they apply to a wide range of problems.

• Model- and data-driven approximation aims at constructing low complexity models in place of a large-scale, infinite dimensional models or directly from input-output data. One importance is that the reduced model should have similar input-output behavior and characteristics as the original model, and that the process in scalable to large amount of data. Most of these development are transferred in the industrial tools provided by MOR Digital Systems: MDSPACK.

• Control design aims at constructing active feedback control schemes and laws, either on the basis of dynamical models (model-driven) or input-output data (data-driven).

• Model analysis aims at emphasizing some properties and characteristics of a (controlled) dynamical system, such as stability, energy... including large-scale and infinite dimensional models.

A important part of my research is dedicated in the numerical tools and software construction, involving studies in numerical analysis, functional analysis and linear algebra