Model-based and data-driven model-reference control: a comparative analysis

In the scientific literature, two main approaches have been proposed for control system design from data. In the "model-based" approach, a model of the system is first derived from data and then a controller is computed based on the model. In the "data-driven" approach, the controller is directly computed from data. In this work, the above approaches are compared from a novel perspective. The main finding of the paper is that, although from the standard perspective of parameter variance analysis the model-based approach is always statistically more efficient, the data-driven controller might outperform the model-based solution for what concerns the final control cost.