Aggregation-based model reduction for tokamak control

The use of model reduction schemes based on eigenstructure analysis is shown to be useful in the study of control problems in tokamak experiments. In particular, state aggregation techniques allow to produce reduced-order models where the physical meaning of the state variables is preserved. This turns out to be useful to obtain interesting interpretations in terms of physical quantities of the simplified model, its parameters, and the approximations involved.