Data-Driven Modelling and Control


New developments in many fields, which include biology and medicine, communications, computers and networks, create new systems that require a significant expansion of control design methodologies.  These new systems are generally large scale, distributed, interconnected, time varying and stochastic. A common feature is that there is an enormous amount of data, which can be processed and used to provide high performance in the presence of uncertainties. The use of direct data-driven controller design methods can relieve the modeling task of these complicated systems. Moreover, model-based controller design methods should take into account the parametric uncertainty and time-varying characteristics of these type of systems.


 Time-Domain Methods 

Frequency-Domain Methods
Distributed Control of Smart Grids Mechatronic Systems