Resonant power converters offer improved levels of efficiency and density. In order to implement such systems, advanced control techniques are required take the most converter. this context, model predictive arises as a powerful tool that is able consider nonlinearities constraints, but it requires solution complex optimization problems or strong simplifying assumptions hinder its application i...

In this paper, direct model predictive control (DMPC) of the noninverting buck-boost DC-DC converter with magnetic coupling between input and output is proposed. Unlike most other converters, subject has advantage exhibiting minimum phase behavior in boost mode. However, a major issue that arises classical dead zone near transition buck The reason for practically unrealizable duty cycles, which...

We employ a novel data-enabled predictive control (DeePC) algorithm in voltage source converter (VSC)-based high-voltage DC (HVDC) stations to perform safe and optimal wide-area for power system oscillation damping. Conventional is model based. However, practice, detailed accurate parametric models are rarely available. In contrast, the DeePC uses only input-output data measured from unknown pr...