Control systems engineers face new large scale interconnected system of systems that are uncertain, time-varying and nonlinear. The structure of these systems is unknown and can hardly be represented by low-order parametric models that usually used in model-based controller design methods. On the other hand, a huge amount of operational data are available and can be used directly to compute low-order fixed structure distributed controllers. Development of new direct data-driven control algorithms for distributed controllers that guarantee good performance and robustness of the systems in the presence of uncertainties is the main research axis of the Data-Driven Modelling and Control Group. The methods can be applied to distributed control of large-scale energy systems as well as high precision mechatronic systems.